Apparatus for providing derived glucose information utilizing non-invasive physiological sensors

ABSTRACT

Systems and methods for non-invasively determining parameters related to blood glucose are disclosed. Embodiments are disclosed wherein a wearable sensor device comprises non-invasive sensors generating various sensed data which is then utilized to determine a glucose-related parameter.

CROSS REFERENCE TO A RELATED APPLICATION

This application is a continuation of co-pending U.S. patent applicationSer. No. 12/217,299, filed Jul. 2, 2008, which, in turn, is acontinuation-in-part of U.S. patent application Ser. No. 10/682,293,filed Oct. 9, 2003 which, again in turn, claims the benefit of U.S.Provisional Patent Application No. 60/417,163, filed Oct. 9, 2002. U.S.patent application Ser. No. 12/217,299, filed Jul. 2, 2008 claims thebenefit of U.S. Provisional Patent Application No. 60/958,516, filedJul. 6, 2007. All applications referred to above are incorporated hereinby reference.

GOVERNMENT LICENSE RIGHTS

This invention was made with government support under W81XWH-06-1-0734awarded by USA MED RESEARCH ACQ ACTIVITY. The government has certainrights in the invention.

FIELD OF THE INVENTION

The present invention relates to methods and apparatuses for measuring astate parameter, in particular glucose, of an individual using signalsbased on one or more sensors. The present invention also relates tovarious methods for making such apparatuses.

BACKGROUND OF THE INVENTION

Type II diabetes is approaching “epidemic” incidence in the UnitedStates, driven in large part by a remarkable rise in obesity rates overthe past 15 years. According to the American Diabetes Association (ADA),18.2 million people in the United States, or 6.3% of the population havediabetes. From 1980 through 2003, the number of Americans with diabetesmore than doubled (Centers for Disease Control, 2005). Nearly two-thirdsof all Americans are now classified as either overweight or obese, acondition that puts them at risk for this kind of diabetes.

The direct medical costs of diabetes and its secondary complicationsaccounted for $160 billion in 2002. The indirect effects of the disease,which include lost workdays, restricted activity days, mortality, andpermanent disability, were estimated to be $39.8 billion for the sameyear. These figures underestimate the effects of diabetes on society, asthey do not include the decreased quality of life and resultant pain andsuffering that accompany the disease, nor the economic value of unpaidcaregivers or the medical expenses of people with undiagnosed diabetes.

The major burden of this disease to the patient and to health careresources is due to the long-term complications that are catastrophic tothe eyes, kidneys, nerves, heart and limbs. There is now good evidencethat at least the microangiopathy of diabetes is related to the durationand severity of hyperglycaemia. In theory, returning blood glucoselevels to normal by replacement insulin injections and other treatmentsin diabetes should prevent complications, therefore, it is extremelyimportant to monitor blood glucose levels.

Diabetic patients currently measure their won blood glucose by obtainingfinger-prick capillary samples and applying the blood to a reagent stripfor analysis in a portable meter. Glucose selfmonitoring has had a majorimpact on improving diabetes care in the last few decades, thedisadvantages of this technology include the fact that the discomfort ofobtaining a blood sample leads to non-compliance, that testing cannot beperformed during sleeping, and that intermittent testing may missepisodes of hyper- and hypo-glycemia. The ideal in-vivo glucosemonitoring technology should therefore be non-invasive and continuous.

Billions of dollars of public and private sources have been spent on theresearch and development of noninvasive or long-term implantable glucosemonitoring. However, each of these techniques has significant obstaclesand weaknesses. For example, the major problem in measuring glucoseconcentration in interstitial fluid is that there is a “lag time”.Furthermore, the attachment and measurement in interstitial fluid canalso cause skin irritations and rashes. For most implanted orsemi-invasive techniques, bio-compatibility is the major problem; evensubcutaneously implanted devices with prolonged contact will provoke aninflammatory response.

Prior art techniques direct measurement of blood glucose via either thedirect detection of glucose in bodily fluids or indirect measurementsvia a single physical signal that is dependent on the blood glucoselevel (e.g., the near infra-red techniques). In general, directmeasurement techniques all suffer from problems of invasiveness;indirect techniques suffer from the problem of accuracy.

There is thus a need for a non-invasive and accurate approach for themeasurement of blood glucose levels.

SUMMARY OF THE INVENTION

The invention utilizes machine learning techniques to indirectly predictglucose levels using a noninvasive, multi-sensor, comfortable,continuously worn body-monitor. By combining signals from differentsensors that themselves do not directly measure blood glucose signalsbut instead measures aspects of physiology that are related to bloodglucose levels, the invention can obtain an accurate prediction of bloodglucose levels without invasive measurements.

The present invention relates generally to an apparatus for measuring astate parameter, such as blood glucose levels, of an individualincluding a processor, at least two sensors in electronic communicationwith the processor, at least one of the sensors being a physiologicalsensor, and a memory for storing software executable by the processor.The software includes instructions for collecting a plurality of sensorsignals from the at least two sensors, and utilizing a first set ofsignals based on one or more of the plurality of sensor signals in afirst function, the first function determining how a second set ofsignals based on one or more of the plurality of sensor signals isutilized in one or more second functions, each of the one or more secondfunctions having an output, wherein one or more of the outputs are usedto predict the state parameter of the individual.

The present invention also relates to a method of measuring a stateparameter of an individual, including collecting a plurality of sensorsignals from at least two sensors in electronic communication with asensor device worn on a body of the individual, at least one of thesensors being a physiological sensor, and utilizing a first set ofsignals based on one or more of the plurality of sensor signals in afirst function, the first function determining how a second set ofsignals based on one or more of the plurality of sensor signals isutilized in one or more second functions, each of the one or more secondfunctions having an output, wherein one or more of the outputs are usedto predict the state parameter of the individual.

In one embodiment of either the apparatus or method, the first functionrecognizes one or more contexts based on the first set of signals andone or more of the second functions is chosen based on the one or morerecognized contexts. The outputs of the chosen second functions are usedto predict the state parameter of the individual. In another embodiment,the first function recognizes each of a plurality of contexts based onthe first set of signals and each of the one or more second functionscorresponds to one of the contexts. The first function assigns a weightto each of the one or more second functions based on a recognitionprobability associated with the corresponding context, and the outputsof the one or more second functions and the weights are used to predictthe state parameter of the individual. The outputs may be combined in apost processing step to predict the state parameter. In addition, ineither the apparatus or the method, the state parameter may be caloricexpenditure the second functions may be regression algorithms, thecontexts may comprise rest and active and, the first function maycomprise a naïve Bayesian classifier. Where the state parameter iscaloric expenditure, caloric consumption data for the individual may begenerated and information based on the caloric expenditure data and thecaloric consumption data may be displayed, such as energy balance data,rate of weight loss or gain, or information relating to one or moregoals of the individual.

In one embodiment of the apparatus, the processor and the memory areincluded in a wearable sensor device. In another embodiment, theapparatus includes a wearable sensor device, the processor and thememory being included in a computing device located separately from thesensor device, wherein the sensor signals are transmitted from thesensor device to the computing device.

The present invention also relates to a method of making software for anapparatus for measuring a state parameter of an individual includingproviding a first sensor device, the first sensor device receiving aplurality of signals from at least two sensors, using the first sensordevice to create a first function and one or more second functions, eachof the one or more second functions having an output, the first functionutilizing a first set of signals based on one or more of the pluralityof sensor signals to determine how a second set of signals based on oneor more of the plurality of sensor signals is utilized in the one ormore second functions, wherein one or more of the outputs are used topredict the state parameter of the individual. The method furtherincludes creating the software including instructions for: (i) receivinga second plurality of signals collected by a second sensor devicesubstantially structurally identical to the first sensor device for aperiod of time; (ii) utilizing a third set of signals based on one ormore of the second plurality of sensor signals in the first function todetermine how a fourth set of signals based on one or more of the secondplurality of sensor signals is utilized in the one or more secondfunctions; and (iii) utilizing the one or more outputs produced by theone or more second functions from the fourth set of signals to predictthe state parameter of the individual. In the method, the step of usingthe sensor device to create the first function and the one or moresecond functions may include gathering a first set of the plurality ofsignals under conditions where the state parameter is present,contemporaneously gathering gold standard data relating to the stateparameter, and using one or more machine learning techniques to generatethe first function and the one or more second functions from the firstset of the plurality of signals and the gold standard data. In addition,the first function may recognize one or more contexts based on the firstset of signals and one or more of the second functions may be chosenbased on the one or more recognized contexts, wherein the outputs of thechosen second functions are used to predict the state parameter of theindividual. Alternatively, the first function may recognize each of aplurality of contexts based on the first set of signals and each of theone or more second functions may correspond to one of the contexts,wherein the first function assigns a weight to each of the one or moresecond functions based on a recognition probability associated with thecorresponding context, and wherein the outputs of the one or more secondfunctions and the weights are used to predict the state parameter of theindividual.

One specific embodiment of the present invention relates to a method ofmeasuring energy expenditure of an individual including collecting aplurality of sensor signals from at least two of a body motion sensor, aheat flux sensor, a skin conductance sensor, and a skin temperaturesensor, each in electronic communication with a sensor device worn on abody of the individual, and utilizing a first set of signals based onone or more of the plurality of sensor signals in one or more functionsto predict the energy expenditure of the individual. The utilizing stepmay include utilizing the first set of signals in a first function, thefirst function determining how a second set of signals based on one ormore of the plurality of sensor signals is utilized in one or moresecond functions, each of the one or more second functions having anoutput, wherein one or more of the outputs are used to predict theenergy expenditure of the individual. In addition, the collecting stepmay include collecting the plurality of sensor signals from a bodymotion sensor, a heat flux sensor, and a skin conductance sensor, thesecond set of signals comprising a heat flux high gain average variance(HFvar), a vector sum of transverse and longitudinal accelerometer SADs(VSAD), and a galvanic skin response low gain (GSR), wherein the secondfunctions have the form of A*VSAD+B*HF+C*GSR+D*BMR+E, wherein A, B, C, Dand E are constants and BMR is a basal metabolic rate for theindividual.

The present invention also relates to an apparatus for measuring energyexpenditure of an individual including a processor, at least two of abody motion sensor, a heat flux sensor, a skin conductance sensor, and askin temperature sensor in electronic communication with the processor,and a memory storing software executable by the processor. The softwareincludes instructions for collecting a plurality of sensor signals fromthe at least two of a body motion sensor, a heat flux sensor, a skinconductance sensor, and a skin temperature sensor, and utilizing a firstset of signals based on one or more of the plurality of sensor signalsin one or more functions to predict the energy expenditure of theindividual. The utilizing instruction may include utilizing the firstset of signals in a first function, the first function determining how asecond set of signals based on one or more of the plurality of sensorsignals is utilized in one or more second functions, each of the one ormore second functions having an output, wherein one or more of theoutputs are used to predict the energy expenditure of the individual.The collecting instruction may include collecting the plurality ofsensor signals from a body motion sensor, a heat flux sensor, and a skinconductance sensor, the second set of signals comprising a heat fluxhigh gain average variance (HFvar), a vector sum of transverse andlongitudinal accelerometer SADs (VSAD), and a galvanic skin response lowgain (GSR), wherein the second functions have the form ofA*VSAD+B*HF+C*GSR+D*BMR+E, wherein A, B, C, D and E are constants andBMR is a basal metabolic rate for the individual.

The present invention also relates to a method of making software for anapparatus for measuring energy expenditure of an individual, includingproviding a first sensor device, the first sensor device receiving aplurality of signals from at least two of a body motion sensor, a heatflux sensor, a skin conductance sensor, and a skin temperature sensor,and using the first sensor device to create one or more functions thatpredict the energy expenditure of the individual using a first set ofsignals based on one or more of the plurality of sensor signals. Themethod further includes creating the software including instructionsfor: (i) receiving a second plurality of signals collected by a secondsensor device substantially structurally identical to the first sensordevice for a period of time, the second sensor device receiving thesecond plurality of signals from at least two of a body motion sensor, aheat flux sensor, a skin conductance sensor, and a skin temperaturesensor; and (ii) utilizing a second set of signals based on one or moreof the second plurality of sensor signals in the one or more functionsto predict the energy expenditure of the individual. The step of usingthe sensor device to create the one or more functions may includegathering a first set of the plurality of signals under conditions whereenergy expenditure data for the individual is present, contemporaneouslygathering gold standard data relating to the energy expenditure data forthe individual, and using one or more machine learning techniques togenerate the one or more functions from the first set of the pluralityof signals and the gold standard data. In addition, the utilizinginstruction may include utilizing the second set of signals in a firstfunction, the first function determining how a third set of signalsbased on one or more of the second plurality of sensor signals isutilized in one or more second functions, each of the one or more secondfunctions having an output; wherein one or more of the outputs are usedto predict the energy expenditure of the individual.

In yet another embodiment, the present invention relates to an apparatusfor automatically measuring a first state parameter of an individual,including a processor, one or more sensors for generating one or moresignals over a period of time, the processor receiving the one or moresignals, and a memory storing software executable by the processor. Thesoftware includes instructions for inputting one or more signal channelsbased on the one or more signals into a first function having a firstoutput that predicts one or more second state parameters of theindividual and either the first state parameter or an indicator of thefirst state parameter, wherein the first state parameter may be obtainedfrom the indicator based on a first relationship between the first stateparameter and the indicator, inputting the one or more signal channelsinto a second function having a second output that predicts the one ormore second state parameters but not the first state parameter or theindicator of the first state parameter, and obtaining either the firststate parameter or the indicator from the first and second outputs basedon a second relationship between the first function and the secondfunction, and, if the indicator is obtained, obtaining the first stateparameter from the indicator based on the first relationship.

The present invention also relates to a method of automaticallymeasuring a first state parameter of an individual, including collectingfor a period of time one or more signals from one or more sensors inelectronic communication with a sensor device worn on a body of theindividual, inputting one or more signal channels based on the one ormore signals into a first function having a first output that predictsone or more second state parameters of the individual and either thefirst state parameter or an indicator of the first state parameter,wherein the first state parameter may be obtained from the indicatorbased on a first relationship between the first state parameter and theindicator, inputting the one or more signal channels into a secondfunction having a second output that predicts the one or more secondstate parameters but not the first state parameter or the indicator ofthe first state parameter, and obtaining either the first stateparameter or the indicator from the first and second outputs based on asecond relationship between the first function and the second function,and, if the indicator is obtained, obtaining the first state parameterfrom the indicator based on the first relationship.

In either the method or the apparatus, the first state parameter may bea number of calories consumed by the individual during the period oftime. In such an embodiment, the indicator may include a first effect onthe body of food consumed, and in particular, the indicator may be thethermic effect of food. In the case of thermic effect of food, the firstoutput may comprise total energy expenditure, wherein the one or moresecond state parameters include basal metabolic rate, activity energyexpenditure and adaptive thermogenesis, and the first state parametermay be obtained from the indicator by dividing the indicator by 0.1. Inone specific embodiment, the software further includes instructions forgenerating caloric expenditure data for the individual for the period oftime from one or more of the one or more signal channels and displayinginformation based on the caloric expenditure data and the number ofcalories consumed by the individual. The apparatus may include adisplay, such as part of a separate I/O device, for displaying theinformation based on the caloric expenditure data and the number ofcalories consumed by the individual.

In yet another embodiment, the present invention relates to a method ofmaking software for an apparatus for automatically measuring a firststate parameter of an individual. The method includes providing a firstsensor device, the first sensor device receiving one or more signalsfrom one or more sensors, using the first sensor device to create afirst function having a first output that predicts one or more secondstate parameters of the individual and either the first state parameteror an indicator of the first state parameter, wherein the first stateparameter may be obtained from the indicator based on a firstrelationship between the first state parameter and the indicator, thefirst function taking as inputs one or more signal channels based on theone or more signals, and using the first sensor device to create asecond function having a second output that predicts the one or moresecond state parameters but not the first state parameter or theindicator of the first state parameter, the second function taking asinputs the one or more signal channels. The method further includescreating the software including instructions for: (i) receiving a secondone or more signals collected by a second sensor device substantiallystructurally identical to the first sensor device for a period of time;(ii) inputting a second one or more signal channels based on the secondone or more signals into the first function and the second function forgenerating the first output and the second output, respectively; and(iii) obtaining either the first state parameter or the indicator fromthe first and second outputs generated in the inputting step based on asecond relationship between the first function and the second function,and, if the indicator is obtained, obtaining the first state parameterfrom the indicator based on the first relationship. The step of usingthe sensor device to create the first function may include gathering afirst set of the one or more signals under conditions where the secondstate parameters and either the first state parameter or the indicatorare present, contemporaneously gathering gold standard data relating tothe second state parameters and either the first state parameter or theindicator, and using one or more machine learning techniques to generatethe first function from the first set of one or more signals and thegold standard data, and the step of using the sensor device to createthe second function may include gathering a second set of the one ormore signals under conditions where neither the first state parameternor the indicator are present, contemporaneously gathering second goldstandard data relating to the second state parameters but not the firststate parameter or the indicator, and using one or more machine learningtechniques to generate the second function from the second set of one ormore signals and the second gold standard data.

In still another alternate embodiment, the present invention relates toa method of measuring caloric consumption of an individual for a timeperiod, including determining a weight differential for the individualbetween a beginning of the time period and an end of the time period,multiplying the weight differential by a constant, such as 3500, toobtain a caloric differential, measuring a caloric expenditure of theindividual for the time period using a wearable sensor device having oneor more sensors, and determining the caloric consumption from thecaloric differential and the caloric expenditure. The step of measuringthe caloric expenditure may comprises collecting a plurality of sensorsignals from at least two sensors in electronic communication with thesensor device, at least one of the sensors being a physiological sensor,and utilizing a first set of signals based on one or more of theplurality of sensor signals in a first function, the first functiondetermining how a second set of signals based on one or more of theplurality of sensor signals is utilized in one or more second functions,each of the one or more second functions having an output, wherein oneor more of the outputs are used to predict the caloric expenditure.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features and advantages of the present invention will beapparent upon consideration of the following detailed description of thepresent invention, taken in conjunction with the following drawings, inwhich like reference characters refer to like parts, and in which:

FIG. 1 is a diagram of an embodiment of a system for monitoringphysiological data and lifestyle over an electronic network according tothe present invention;

FIG. 2 is a block diagram of an embodiment of the sensor device shown inFIG. 1;

FIG. 3 is a block diagram of an embodiment of the central monitoringunit shown in FIG. 1;

FIG. 4 is a block diagram of an alternate embodiment of the centralmonitoring unit shown in FIG. 1;

FIG. 5 is a representation of a preferred embodiment of the HealthManager web page according to an aspect of the present invention;

FIG. 6 is a representation of a preferred embodiment of the nutritionweb page according to an aspect of the present invention;

FIG. 7 is a representation of a preferred embodiment of the activitylevel web page according to an aspect of the present invention;

FIG. 8 is a representation of a preferred embodiment of the mindcentering web page according to an aspect of the present invention;

FIG. 9 is a representation of a preferred embodiment of the sleep webpage according to an aspect of the present invention;

FIG. 10 is a representation of a preferred embodiment of the dailyactivities web page according to an aspect of the present invention;

FIG. 11 is a representation of a preferred embodiment of the HealthIndex web page according to an aspect of the present invention;

FIG. 12 is a front view of a specific embodiment of the sensor deviceshown in FIG. 1;

FIG. 13 is a back view of a specific embodiment of the sensor deviceshown in FIG. 1;

FIG. 14 is a side view of a specific embodiment of the sensor deviceshown in FIG. 1;

FIG. 15 is a bottom view of a specific embodiment of the sensor deviceshown in FIG. 1;

FIGS. 16 and 17 are front perspective views of a specific embodiment ofthe sensor device shown in FIG. 1;

FIG. 18 is an exploded side perspective view of a specific embodiment ofthe sensor device shown in FIG. 1;

FIG. 19 is a side view of the sensor device shown in FIGS. 12 through 18inserted into a battery recharger unit;

FIG. 20 is a block diagram illustrating all of the components eithermounted on or coupled to the printed circuit board forming a part of thesensor device shown in FIGS. 12 through 18;

FIG. 21 is a block diagram of an apparatus for monitoring health,wellness and fitness according to an alternate embodiment of the presentinvention.

FIG. 22 is a front view of an alternate embodiment of a sensor deviceaccording to the present invention;

FIG. 23 is a back view of an alternate embodiment of a sensor deviceaccording to the present invention;

FIG. 24 is a cross-sectional view of the sensor device shown in FIG. 22taken along lines A-A;

FIG. 25 is a cross-sectional view of the sensor device shown in FIG. 22taken along lines B-B;

FIG. 26 is a cross-sectional view of the sensor device shown in FIG. 22taken along lines A-A showing the internal components of the housing ofthe sensor device;

FIG. 27 is a block diagram illustrating the components mounted on orcoupled to the printed circuit board forming a part of an embodiment ofthe sensor device shown in FIGS. 22 through 26;

FIG. 28 is a front view of an alternate embodiment of a sensor deviceaccording to the present invention including an LCD;

FIG. 29 is a block diagram illustrating the components mounted on orcoupled to the printed circuit board forming a part of an alternateembodiment of the sensor device shown in FIGS. 22 through 26;

FIGS. 30 and 31 are isometric views of an alternate embodiment of asensor device according to the present invention having a housingadapted to be removably attached to a flexible section;

FIG. 32 is an isometric view of a further alternate embodiment of asensor device according to the present invention having a housingadapted to be removably attached to a flexible section;

FIG. 33 is an isometric view of an embodiment of a sensor device havingadjustable operating parameters according to an aspect of the presentinvention;

FIG. 34 is an isometric view of an alternate embodiment of a sensordevice according to the present invention having a housing having anadhesive material on an external surface thereof for removably attachingthe housing to the body;

FIGS. 35A and B are cross-sectional views of a housing for a prior artsensor device;

FIGS. 35C through H are cross-sectional views of various embodiments ofa housing for a sensor device according to an aspect of the presentinvention taken along lines C-C in FIG. 23.

FIG. 36A is a cross-sectional view of a housing for a prior art sensordevice;

FIGS. 36B through H are cross-sectional views of various embodiments ofa housing for a sensor device according to an aspect of the presentinvention taken along lines D-D in FIG. 23;

FIG. 37 is an isometric view of an embodiment of a housing for a sensordevice according to the present invention having a bottom or innersurface having a concavity in one direction and a convexity in anotherdirection;

FIGS. 38A through D are cross-sectional views of a housing for a sensordevice having a flat top surface and flat lateral ends;

FIGS. 39A through F are cross-sectional views of various embodiments ofa housing for a sensor device having surfaces designed to deflectobjects and prevent movement of the housing;

FIG. 39G is a cross-sectional view of the housing shown in FIG. 39Eattached to a flexible section;

FIG. 40 is a top plan view of a data input and output device accordingto the present invention;

FIG. 41 is a partial cross-sectional view of the data input and outputdevice shown in FIG. 40 taken along lines A-A in FIG. 40;

FIG. 42 is a block diagram illustrating the operation of prior artsoftware that enables a prior art input device having a dial and abutton to control the operation of a computer by identifying andselecting hot spots;

FIGS. 43A-F is a top plan view of a data input and output deviceaccording to an embodiment of the present invention in which energyrelated data for an individual is collected or generated by the datainput and output device and a sensor device in electrical communicationtherewith and displayed by the data input and output device on an LCDprovided thereon;

FIGS. 43G and H are a plan views of interfaces for entering nutritioninformation into a data input and output device according to analternate embodiment of the present invention;

FIGS. 43I and J are scatter plots between estimates of the caloriccontent in meals consumed using an embodiment of the present inventionand caloric content computed from full diet diary entries;

FIG. 44 is a block diagram showing the components attached or otherwisecoupled to a printed circuit board housed within a data input and outputdevice according to an embodiment of the present invention;

FIG. 45 is a partial cross-sectional view of a data input and outputdevice according to an alternate embodiment of the present inventionhaving one or more sensors that enable it to collect data indicative ofphysiological and/or contextual parameters;

FIG. 46 is a block diagram of an alternate embodiment of the presentinvention in which a data input and output device acts as a hub orterminal for collection and, optionally, processing of data from avariety of sources;

FIG. 47 is a block diagram showing the format of algorithms that aredeveloped according to an aspect of the present invention; and

FIG. 48 is a block diagram illustrating an example algorithm forpredicting energy expenditure according to the present invention.

FIG. 49 shows a scatter plot between measured blood glucose level andestimated blood glucose levels in an embodiment of the invention.

FIG. 50A shows a Clarke error grid analysis between an embodiment of thepresent invention and continuous glucose monitor values.

FIG. 50B shows a Clarke error grid analysis between an embodiment of thepresent invention and continuous glucose monitor values.

FIG. 51 shows the contribution of the sensor-based variables and thefood-intake-based variables in an embodiment of the present invention.

FIG. 52 depicts a Clarke error grid analysis between model estimates andCGM values for an embodiment of the present invention.

FIG. 53 depicts a Clarke error grid analysis between model estimates andfinger stick glucose values in an embodiment of the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

In general, according to the present invention, data relating to thephysiological state, the lifestyle and certain contextual parameters ofan individual is collected and transmitted, either subsequently or inreal-time, to a site, preferably remote from the individual, where it isstored for later manipulation and presentation to a recipient,preferably over an electronic network such as the Internet. Contextualparameters as used herein means parameters relating to the environment,surroundings and location of the individual, including, but not limitedto, air quality, sound quality, ambient temperature, global positioningand the like. Referring to FIG. 1, located at user location 5 is sensordevice 10 adapted to be placed in proximity with at least a portion ofthe human body. Sensor device 10 is preferably worn by an individualuser on his or her body, for example as part of a garment such as a formfitting shirt, or as part of an arm band or the like. Sensor device 10,includes one or more sensors, which are adapted to generate signals inresponse to physiological characteristics of an individual, and amicroprocessor. Proximity as used herein means that the sensors ofsensor device 10 are separated from the individual's body by a materialor the like, or a distance such that the capabilities of the sensors arenot impeded.

Sensor device 10 generates data indicative of various physiologicalparameters of an individual, such as the individual's heart rate, pulserate, beat-to-beat heart variability, EKG or ECG, respiration rate, skintemperature, core body temperature, heat flow off the body, galvanicskin response or GSR, EMG, EEG, EOG, blood pressure, body fat, hydrationlevel, activity level, oxygen consumption, glucose or blood sugar level,body position, pressure on muscles or bones, and UV radiation exposureand absorption. In certain cases, the data indicative of the variousphysiological parameters is the signal or signals themselves generatedby the one or more sensors and in certain other cases the data iscalculated by the microprocessor based on the signal or signalsgenerated by the one or more sensors. Methods for generating dataindicative of various physiological parameters and sensors to be usedtherefor are well known. Table 1 provides several examples of such wellknown methods and shows the parameter in question, the method used, thesensor device used, and the signal that is generated. Table 1 alsoprovides an indication as to whether further processing based on thegenerated signal is required to generate the data.

TABLE 1 Further Parameter Method Sensor Signal Processing Heart Rate EKG2 Electrodes DC Voltage Yes Pulse Rate BVP LED Emitter and Change inResistance Yes Optical Sensor Beat-to-Beat Heart Rate 2 Electrodes DCVoltage Yes Variability EKG Skin Surface 3-10 Electrodes DC Voltage NoPotentials Respiration Rate Chest Volume Strain Gauge Change inResistance Yes Change Skin Temperature Surface Thermistors Change inResistance Yes Temperature Probe Core Temperature Esophageal orThermistors Change in Resistance Yes Rectal Probe Heat Flow Heat FluxThermopile DC Voltage Yes Galvanic Skin Skin Conductance 2 ElectrodesChange in Resistance No Response EMG Skin Surface 3 Electrodes DCVoltage No Potentials EEG Skin Surface Multiple Electrodes DC VoltageYes Potentials EOG Eye Movement Thin Film DC Voltage Yes PiezoelectricSensors Blood Pressure Non-Invasive Electronic Change in Resistance YesKorotkuff Sounds Sphygromarometer Body Fat Body Impedance 2 ActiveElectrodes Change in Impedance Yes Activity in Body MovementAccelerometer DC Voltage, Yes Interpreted G Capacitance Changes Shocksper Minute Oxygen Oxygen Uptake Electro-chemical DC Voltage Change YesConsumption Glucose Level Non-Invasive Electro-chemical DC VoltageChange Yes Body Position (e.g. N/A Mercury Switch DC Voltage Change Yessupine, erect, Array sitting) Muscle Pressure N/A Thin Film DC VoltageChange Yes Piezoelectric Sensors UV Radiation N/A UV Sensitive Photo DCVoltage Change Yes Absorption Cells

The types of data listed in Table 1 are intended to be examples of thetypes of data that can be generated by sensor device 10. It is to beunderstood that other types of data relating to other parameters can begenerated by sensor device 10 without departing from the scope of thepresent invention.

The microprocessor of sensor device 10 may be programmed to summarizeand analyze the data. For example, the microprocessor can be programmedto calculate an average, minimum or maximum heart rate or respirationrate over a defined period of time, such as ten minutes. Sensor device10 may be able to derive information relating to an individual'sphysiological state based on the data indicative of one or morephysiological parameters. The microprocessor of sensor device 10 isprogrammed to derive such information using known methods based on thedata indicative of one or more physiological parameters. Table 2provides examples of the type of information that can be derived, andindicates some of the types of data that can be used therefor.

TABLE 2 Derived Information Data Used Ovulation Skin temperature, coretemperature, oxygen consumption Sleep onset/wake Beat-to-beatvariability, heart rate, pulse rate, respiration rate, skin temperature,core temperature, heat flow, galvanic skin response, EMG, EEG, EOG,blood pressure, oxygen consumption Calories burned Heart rate, pulserate, respiration rate, heat flow, activity, oxygen consumption Basalmetabolic rate Heart rate, pulse rate, respiration rate, heat flow,activity, oxygen consumption Basal temperature Skin temperature, coretemperature Activity level Heart rate, pulse rate, respiration rate,heat flow, activity, oxygen consumption Stress level EKG, beat-to-beatvariability, heart rate, pulse rate, respiration rate, skin temperature,heat flow, galvanic skin response, EMG, EEG, blood pressure, activity,oxygen consumption Relaxation level EKG, beat-to-beat variability, heartrate, pulse rate, respiration rate, skin temperature, heat flow,galvanic skin response, EMG, EEG, blood pressure, activity, oxygenconsumption Maximum oxygen consumption rate EKG, heart rate, pulse rate,respiration rate, heat flow, blood pressure, activity, oxygenconsumption Rise time or the time it takes to rise from Heart rate,pulse rate, heat flow, oxygen consumption a resting rate to 85% of atarget maximum Time in zone or the time heart rate was Heart rate, pulserate, heat flow, oxygen consumption above 85% of a target maximumRecovery time or the time it takes heart Heart rate, pulse rate, heatflow, oxygen consumption rate to return to a resting rate after heartrate was above 85% of a target maximum

Additionally, sensor device 10 may also generate data indicative ofvarious contextual parameters relating to the environment surroundingthe individual. For example, sensor device 10 can generate dataindicative of the air quality, sound level/quality, light quality orambient temperature near the individual, or even the global positioningof the individual. Sensor device 10 may include one or more sensors forgenerating signals in response to contextual characteristics relating tothe environment surrounding the individual, the signals ultimately beingused to generate the type of data described above. Such sensors are wellknown, as are methods for generating contextual parametric data such asair quality, sound level/quality, ambient temperature and globalpositioning.

FIG. 2 is a block diagram of an embodiment of sensor device 10. Sensordevice 10 includes at least one sensor 12 and microprocessor 20.Depending upon the nature of the signal generated by sensor 12, thesignal can be sent through one or more of amplifier 14, conditioningcircuit 16, and analog-to-digital converter 18, before being sent tomicroprocessor 20. For example, where sensor 12 generates an analogsignal in need of amplification and filtering, that signal can be sentto amplifier 14, and then on to conditioning circuit 16, which may, forexample, be a band pass filter. The amplified and conditioned analogsignal can then be transferred to analog-to-digital converter 18, whereit is converted to a digital signal. The digital signal is then sent tomicroprocessor 20. Alternatively, if sensor 12 generates a digitalsignal, that signal can be sent directly to microprocessor 20.

A digital signal or signals representing certain physiological and/orcontextual characteristics of the individual user may be used bymicroprocessor 20 to calculate or generate data indicative ofphysiological and/or contextual parameters of the individual user.Microprocessor 20 is programmed to derive information relating to atleast one aspect of the individual's physiological state. It should beunderstood that microprocessor 20 may also comprise other forms ofprocessors or processing devices, such as a microcontroller, or anyother device that can be programmed to perform the functionalitydescribed herein.

The data indicative of physiological and/or contextual parameters can,according to one embodiment of the present invention, be sent to memory22, such as flash memory, where it is stored until uploaded in themanner to be described below. Although memory 22 is shown in FIG. 2 as adiscrete element, it will be appreciated that it may also be part ofmicroprocessor 20. Sensor device 10 also includes input/output circuitry24, which is adapted to output and receive as input certain data signalsin the manners to be described herein. Thus, memory 22 of the sensordevice 10 will build up, over time, a store of data relating to theindividual user's body and/or environment. That data is periodicallyuploaded from sensor device 10 and sent to remote central monitoringunit 30, as shown in FIG. 1, where it is stored in a database forsubsequent processing and presentation to the user, preferably through alocal or global electronic network such as the Internet. This uploadingof data can be an automatic process that is initiated by sensor device10 periodically or upon the happening of an event such as the detectionby sensor device 10 of a heart rate below a certain level, or can beinitiated by the individual user or some third party authorized by theuser, preferably according to some periodic schedule, such as every dayat 10:00 p.m. Alternatively, rather than storing data in memory 22,sensor device 10 may continuously upload data in real time.

The uploading of data from sensor device 10 to central monitoring unit30 for storage can be accomplished in various ways. In one embodiment,the data collected by sensor device 10 is uploaded by first transferringthe data to personal computer 35 shown in FIG. 1 by means of physicalconnection 40, which, for example, may be a serial connection such as anRS232 or USB port. This physical connection may also be accomplished byusing a cradle, not shown, that is electronically coupled to personalcomputer 35 into which sensor device 10 can be inserted, as is commonwith many commercially available personal digital assistants. Theuploading of data could be initiated by then pressing a button on thecradle or could be initiated automatically upon insertion of sensordevice 10. The data collected by sensor device 10 may be uploaded byfirst transferring the data to personal computer 35 by means ofshort-range wireless transmission, such as infrared or RF transmission,as indicated at 45.

Once the data is received by personal computer 35, it is optionallycompressed and encrypted by any one of a variety of well known methodsand then sent out over a local or global electronic network, preferablythe Internet, to central monitoring unit 30. It should be noted thatpersonal computer 35 can be replaced by any computing device that hasaccess to and that can transmit and receive data through the electronicnetwork, such as, for example, a personal digital assistant such as thePalm VII sold by Palm, Inc., or the Blackberry 2-way pager sold byResearch in Motion, Inc.

Alternatively, the data collected by sensor device 10, after beingencrypted and, optionally, compressed by microprocessor 20, may betransferred to wireless device 50, such as a 2-way pager or cellularphone, for subsequent long distance wireless transmission to local telcosite 55 using a wireless protocol such as e-mail or as ASCII or binarydata. Local telco site 55 includes tower 60 that receives the wirelesstransmission from wireless device 50 and computer 65 connected to tower60. According to the preferred embodiment, computer 65 has access to therelevant electronic network, such as the Internet, and is used totransmit the data received in the form of the wireless transmission tothe central monitoring unit 30 over the Internet. Although wirelessdevice 50 is shown in FIG. 1 as a discrete device coupled to sensordevice 10, it or a device having the same or similar functionality maybe embedded as part of sensor device 10.

Sensor device 10 may be provided with a button to be used to time stampevents such as time to bed, wake time, and time of meals. These timestamps are stored in sensor device 10 and are uploaded to centralmonitoring unit 30 with the rest of the data as described above. Thetime stamps may include a digitally recorded voice message that, afterbeing uploaded to central monitoring unit 30, are translated using voicerecognition technology into text or some other information format thatcan be used by central monitoring unit 30.

In addition to using sensor device 10 to automatically collectphysiological data relating to an individual user, a kiosk could beadapted to collect such data by, for example, weighing the individual,providing a sensing device similar to sensor device 10 on which anindividual places his or her hand or another part of his or her body, orby scanning the individual's body using, for example, laser technologyor an iStat blood analyzer. The kiosk would be provided with processingcapability as described herein and access to the relevant electronicnetwork, and would thus be adapted to send the collected data to thecentral monitoring unit 30 through the electronic network. A desktopsensing device, again similar to sensor device 10, on which anindividual places his or her hand or another part of his or her body mayalso be provided. For example, such a desktop sensing device could be ablood pressure monitor in which an individual places his or her arm. Anindividual might also wear a ring having a sensor device 10 incorporatedtherein. A base, not shown, could then be provided which is adapted tobe coupled to the ring. The desktop sensing device or the base justdescribed may then be coupled to a computer such as personal computer 35by means of a physical or short range wireless connection so that thecollected data could be uploaded to central monitoring unit 30 over therelevant electronic network in the manner described above. A mobiledevice such as, for example, a personal digital assistant, might also beprovided with a sensor device 10 incorporated therein. Such a sensordevice 10 would be adapted to collect data when mobile device is placedin proximity with the individual's body, such as by holding the devicein the palm of one's hand, and upload the collected data to centralmonitoring unit 30 in any of the ways described herein.

Furthermore, in addition to collecting data by automatically sensingsuch data in the manners described above, individuals can also manuallyprovide data relating to various life activities that is ultimatelytransferred to and stored at central monitoring unit 30. An individualuser can access a web site maintained by central monitoring unit 30 andcan directly input information relating to life activities by enteringtext freely, by responding to questions posed by the web site, or byclicking through dialog boxes provided by the web site. Centralmonitoring unit 30 can also be adapted to periodically send electronicmail messages containing questions designed to elicit informationrelating to life activities to personal computer 35 or to some otherdevice that can receive electronic mail, such as a personal digitalassistant, a pager, or a cellular phone. The individual would thenprovide data relating to life activities to central monitoring unit 30by responding to the appropriate electronic mail message with therelevant data. Central monitoring unit 30 may also be adapted to place atelephone call to an individual user in which certain questions would beposed to the individual user. The user could respond to the questions byentering information using a telephone keypad, or by voice, in whichcase conventional voice recognition technology would be used by centralmonitoring unit 30 to receive and process the response. The telephonecall may also be initiated by the user, in which case the user couldspeak to a person directly or enter information using the keypad or byvoice/voice recognition technology. Central monitoring unit 30 may alsobe given access to a source of information controlled by the user, forexample the user's electronic calendar such as that provided with theOutlook product sold by Microsoft Corporation of Redmond, Wash., fromwhich it could automatically collect information. The data relating tolife activities may relate to the eating, sleep, exercise, mindcentering or relaxation, and/or daily living habits, patterns and/oractivities of the individual. Thus, sample questions may include: Whatdid you have for lunch today? What time did you go to sleep last night?What time did you wake up this morning? How long did you run on thetreadmill today?

Feedback may also be provided to a user directly through sensor device10 in a visual form, for example through an LED or LCD or byconstructing sensor device 10, at least in part, of a thermochromaticplastic, in the form of an acoustic signal or in the form of tactilefeedback such as vibration. Such feedback may be a reminder or an alertto eat a meal or take medication or a supplement such as a vitamin, toengage in an activity such as exercise or meditation, or to drink waterwhen a state of dehydration is detected. Additionally, a reminder oralert can be issued in the event that a particular physiologicalparameter such as ovulation has been detected, a level of caloriesburned during a workout has been achieved or a high heart rate orrespiration rate has been encountered.

As will be apparent to those of skill in the art, it may be possible toAdownload@ data from central monitoring unit 30 to sensor device 10. Theflow of data in such a download process would be substantially thereverse of that described above with respect to the upload of data fromsensor device 10. Thus, it is possible that the firmware ofmicroprocessor 20 of sensor device 10 can be updated or alteredremotely, i.e., the microprocessor can be reprogrammed, by downloadingnew firmware to sensor device 10 from central monitoring unit 30 forsuch parameters as timing and sample rates of sensor device 10. Also,the reminders/alerts provided by sensor device 10 may be set by the userusing the web site maintained by central monitoring unit 30 andsubsequently downloaded to the sensor device 10.

Referring to FIG. 3, a block diagram of an embodiment of centralmonitoring unit 30 is shown. Central monitoring unit 30 includes CSU/DSU70 which is connected to router 75, the main function of which is totake data requests or traffic, both incoming and outgoing, and directsuch requests and traffic for processing or viewing on the web sitemaintained by central monitoring unit 30. Connected to router 75 isfirewall 80. The main purpose of firewall 80 is to protect the remainderof central monitoring unit 30 from unauthorized or malicious intrusions.Switch 85, connected to firewall 80, is used to direct data flow betweenmiddleware servers 95 a through 95 c and database server 110. Loadbalancer 90 is provided to spread the workload of incoming requestsamong the identically configured middleware servers 95 a through 95 c.Load balancer 90, a suitable example of which is the F5 ServerIronproduct sold by Foundry Networks, Inc. of San Jose, Calif., analyzes theavailability of each middleware server 95 a through 95 c, and the amountof system resources being used in each middleware server 95 a through 95c, in order to spread tasks among them appropriately.

Central monitoring unit 30 includes network storage device 100, such asa storage area network or SAN, which acts as the central repository fordata. In particular, network storage device 100 comprises a databasethat stores all data gathered for each individual user in the mannersdescribed above. An example of a suitable network storage device 100 isthe Symmetrix product sold by EMC Corporation of Hopkinton, Mass.Although only one network storage device 100 is shown in FIG. 3, it willbe understood that multiple network storage devices of variouscapacities could be used depending on the data storage needs of centralmonitoring unit 30. Central monitoring unit 30 also includes databaseserver 110 which is coupled to network storage device 100. Databaseserver 110 is made up of two main components: a large scalemultiprocessor server and an enterprise type software server componentsuch as the 8/8i component sold by Oracle Corporation of Redwood City,Calif., or the 506 7 component sold by Microsoft Corporation of Redmond,Wash. The primary functions of database server 110 are that of providingaccess upon request to the data stored in network storage device 100,and populating network storage device 100 with new data. Coupled tonetwork storage device 100 is controller 115, which typically comprisesa desktop personal computer, for managing the data stored in networkstorage device 100.

Middleware servers 95 a through 95 c, a suitable example of which is the22OR Dual Processor sold by Sun Microsystems, Inc. of Palo Alto, Calif.,each contain software for generating and maintaining the corporate orhome web page or pages of the web site maintained by central monitoringunit 30. As is known in the art, a web page refers to a block or blocksof data available on the World-Wide Web comprising a file or fileswritten in Hypertext Markup Language or HTML, and a web site commonlyrefers to any computer on the Internet running a World-Wide Web serverprocess. The corporate or home web page or pages are the opening orlanding web page or pages that are accessible by all members of thegeneral public that visit the site by using the appropriate uniformresource locator or URL. As is known in the art, URLs are the form ofaddress used on the World-Wide Web and provide a standard way ofspecifying the location of an object, typically a web page, on, theInternet. Middleware servers 95 a through 95 c also each containsoftware for generating and maintaining the web pages of the web site ofcentral monitoring unit 30 that can only be accessed by individuals thatregister and become members of central monitoring unit 30. The memberusers will be those individuals who wish to have their data stored atcentral monitoring unit 30. Access by such member users is controlledusing passwords for security purposes. Preferred embodiments of thoseweb pages are described in detail below and are generated usingcollected data that is stored in the database of network storage device100.

Middleware servers 95 a through 95 c also contain software forrequesting data from and writing data to network storage device 100through database server 110. When an individual user desires to initiatea session with the central monitoring unit 30 for the purpose ofentering data into the database of network storage device 100, viewinghis or her data stored in the database of network storage device 100, orboth, the user visits the home web page of central monitoring unit 30using a browser program such as Internet Explorer distributed byMicrosoft Corporation of Redmond, Wash., and logs in as a registereduser. Load balancer 90 assigns the user to one of the middleware servers95 a through 95 c, identified as the chosen middleware server. A userwill preferably be assigned to a chosen middleware server for eachentire session. The chosen middleware server authenticates the userusing any one of many well known methods, to ensure that only the trueuser is permitted to access the information in the database. A memberuser may also grant access to his or her data to a third party such as ahealth care provider or a personal trainer. Each authorized third partymay be given a separate password and may view the member user's datausing a conventional browser. It is therefore possible for both the userand the third party to be the recipient of the data.

When the user is authenticated, the chosen middleware server requests,through database server 110, the individual user's data from networkstorage device 100 for a predetermined time period. The predeterminedtime period is preferably thirty days. The requested data, once receivedfrom network storage device 100, is temporarily stored by the chosenmiddleware server in cache memory. The cached data is used by the chosenmiddleware server as the basis for presenting information, in the formof web pages, to the user again through the user's browser. Eachmiddleware server 95 a through 95 c is provided with appropriatesoftware for generating such web pages, including software formanipulating and performing calculations utilizing the data to put thedata in appropriate format for presentation to the user. Once the userends his or her session, the data is discarded from cache. When the userinitiates a new session, the process for obtaining and caching data forthat user as described above is repeated. This caching system thusideally requires that only one call to the network storage device 100 bemade per session, thereby reducing the traffic that database server 110must handle. Should a request from a user during a particular sessionrequire data that is outside of a predetermined time period of cacheddata already retrieved, a separate call to network storage device 100may be performed by the chosen middleware server. The predetermined timeperiod should be chosen, however, such that such additional calls areminimized. Cached data may also be saved in cache memory so that it canbe reused when a user starts a new session, thus eliminating the need toinitiate a new call to network storage device 100.

As described in connection with Table 2, the microprocessor of sensordevice 10 may be programmed to derive information relating to anindividual's physiological state based on the data indicative of one ormore physiological parameters. Central monitoring unit 30, andpreferably middleware servers 95 a through 95 c, may also be similarlyprogrammed to derive such information based on the data indicative ofone or more physiological parameters.

It is also contemplated that a user will input additional data during asession, for example, information relating to the user's eating orsleeping habits. This additional data is preferably stored by the chosenmiddleware server in a cache during the duration of the user's session.When the user ends the session, this additional new data stored in acache is transferred by the chosen middleware server to database server110 for population in network storage device 100. Alternatively, inaddition to being stored in a cache for potential use during a session,the input data may also be immediately transferred to database server110 for population in network storage device 100, as part of awrite-through cache system which is well known in the art.

Data collected by sensor device 10 shown in FIG. 1 is periodicallyuploaded to central monitoring unit 30. Either by long distance wirelesstransmission or through personal computer 35, a connection to centralmonitoring unit 30 is made through an electronic network, preferably theInternet. In particular, connection is made to load balancer 90 throughCSU/DSU 70, router 75, firewall 80 and switch 85. Load balancer 90 thenchooses one of the middleware servers 95 a through 95 c to handle theupload of data, hereafter called the chosen middleware server. Thechosen middleware server authenticates the user using any one of manywell known methods. If authentication is successful, the data isuploaded to the chosen middleware server as described above, and isultimately transferred to database server 110 for population in thenetwork storage device 100.

Referring to FIG. 4, an alternate embodiment of central monitoring unit30 is shown. In addition to the elements shown and described withrespect to FIG. 3, the embodiment of the central monitoring unit 30shown in FIG. 4 includes a mirror network storage device 120 which is aredundant backup of network storage device 100. Coupled to mirrornetwork storage device 120 is controller 122. Data from network storagedevice 100 is periodically copied to mirror network storage device 120for data redundancy purposes.

Third parties such as insurance companies or research institutions maybe given access, possibly for a fee, to certain of the informationstored in mirror network storage device 120. Preferably, in order tomaintain the confidentiality of the individual users who supply data tocentral monitoring unit 30, these third parties are not given access tosuch user's individual database records, but rather are only givenaccess to the data stored in mirror network storage device 120 inaggregate form. Such third parties may be able to access the informationstored in mirror network storage device 120 through the Internet using aconventional browser program. Requests from third parties may come inthrough CSU/DSU 70, router 75, firewall 80 and switch 85. In theembodiment shown in FIG. 4, a separate load balancer 130 is provided forspreading tasks relating to the accessing and presentation of data frommirror drive array 120 among identically configured middleware servers135 a through 135 c. Middleware servers 135 a through 135 c each containsoftware for enabling the third parties to, using a browser, formulatequeries for information from mirror network storage device 120 throughseparate database server 125. Middleware servers 135 a through 135 calso contain software for presenting the information obtained frommirror network storage device 120 to the third parties over the Internetin the form of web pages. In addition, the third parties can choose froma series of prepared reports that have information packaged alongsubject matter lines, such as various demographic categories.

As will be apparent to one of skill in the art, instead of giving thesethird parties access to the backup data stored in mirror network storagedevice 120, the third parties may be given access to the data stored innetwork storage device 100. Also, instead of providing load balancer 130and middleware servers 135 a through 135 c, the same functionality,although at a sacrificed level of performance, could be provided by loadbalancer 90 and middleware servers 95 a through 95 c.

When an individual user first becomes a registered user or member, thatuser completes a detailed survey. The purposes of the survey are to:identify unique characteristics/circumstances for each user that theymight need to address in order to maximize the likelihood that they willimplement and maintain a healthy lifestyle as suggested by centralmonitoring unit 30; gather baseline data which will be used to setinitial goals for the individual user and facilitate the calculation anddisplay of certain graphical data output such as the Health Indexpistons; identify unique user characteristics and circumstances thatwill help central monitoring unit 30 customize the type of contentprovided to the user in the Health Manager's Daily Dose; and identifyunique user characteristics and circumstances that the Health Managercan guide the user to address as possible barriers to a healthylifestyle through the problem-solving function of the Health Manager.

The specific information to be surveyed may include: key individualtemperamental characteristics, including activity level, regularity ofeating, sleeping, and bowel habits, initial response to situations,adaptability, persistence, threshold of responsiveness, intensity ofreaction, and quality of mood; the user's level of independentfunctioning, i.e., self-organization and management, socialization,memory, and academic achievement skills; the user's ability to focus andsustain attention, including the user's level of arousal, cognitivetempo, ability to filter distractions, vigilance, and self-monitoring;the user's current health status including current weight, height, andblood pressure, most recent general physician visit, gynecological exam,and other applicable physician/healthcare contacts, current medicationsand supplements, allergies, and a review of current symptoms and/orhealth-related behaviors; the user's past health history, i.e.,illnesses/surgeries, family history, and social stress events, such asdivorce or loss of a job, that have required adjustment by theindividual; the user's beliefs, values and opinions about healthpriorities, their ability to alter their behavior and, what mightcontribute to stress in their life, and how they manage it; the user'sdegree of self-awareness, empathy, empowerment, and self-esteem, and theuser's current daily routines for eating, sleeping, exercise, relaxationand completing activities of daily living; and the user's perception ofthe temperamental characteristics of two key persons in their life, forexample, their spouse, a friend, a co-worker, or their boss, and whetherthere are clashes present in their relationships that might interferewith a healthy lifestyle or contribute to stress.

Each member user will have access, through the home web page of centralmonitoring unit 30, to a series of web pages customized for that user,referred to as the Health Manager. The opening Health Manager web page150 is shown in FIG. 5. The Health Manager web pages are the mainworkspace area for the member user. The Health Manager web pagescomprise a utility through which central monitoring unit 30 providesvarious types and forms of data, commonly referred to as analyticalstatus data, to the user that is generated from the data it collects orgenerates, namely one or more of: the data indicative of variousphysiological parameters generated by sensor device 10; the data derivedfrom the data indicative of various physiological parameters; the dataindicative of various contextual parameters generated by sensor device10; and the data input by the user. Analytical status data ischaracterized by the application of certain utilities or algorithms toconvert one or more of the data indicative of various physiologicalparameters generated by sensor device 10, the data derived from the dataindicative of various physiological parameters, the data indicative ofvarious contextual parameters generated by sensor device 10, and thedata input by the user into calculated health, wellness and lifestyleindicators. For example, based on data input by the user relating to thefoods he or she has eaten, things such as calories and amounts ofproteins, fats, carbohydrates, and certain vitamins can be calculated.As another example, skin temperature, heart rate, respiration rate, heatflow and/or GSR can be used to provide an indicator to the user of hisor her stress level over a desired time period. As still anotherexample, skin temperature, heat flow, beat-to-beat heart variability,heart rate, pulse rate, respiration rate, core temperature, galvanicskin response, EMG, EEG, EOG, blood pressure, oxygen consumption,ambient sound and body movement or motion as detected by a device suchas an accelerometer can be used to provide indicators to the user of hisor her sleep patterns over a desired time period.

Located on the opening Health Manager web page 150 is Health Index 155.Health Index 155 is a graphical utility used to measure and providefeedback to member users regarding their performance and the degree towhich they have succeeded in reaching a healthy daily routine suggestedby central monitoring unit 30. Health Index 155 thus provides anindication for the member user to track his or her progress. HealthIndex 155 includes six categories relating to the user's health andlifestyle: Nutrition, Activity Level, Mind Centering, Sleep, DailyActivities and How You Feel. The Nutrition category relates to what,when and how much a person eats and drinks. The Activity Level categoryrelates to how much a person moves around. The Mind Centering categoryrelates to the quality and quantity of time a person spends engaging insome activity that allows the body to achieve a state of profoundrelaxation while the mind becomes highly alert and focused. The Sleepcategory relates to the quality and quantity of a person's sleep. TheDaily Activities category relates to the daily responsibilities andhealth risks people encounter. Finally, the How You Feel categoryrelates to the general perception that a person has about how they feelon a particular day. Each category has an associated level indicator orpiston that indicates, preferably on a scale ranging from poor toexcellent, how the user is performing with respect to that category.

When each member user completes the initial survey described above, aprofile is generated that provides the user with a summary of his or herrelevant characteristics and life circumstances. A plan and/or set ofgoals is provided in the form of a suggested healthy daily routine. Thesuggested healthy daily routine may include any combination of specificsuggestions for incorporating proper nutrition, exercise, mindcentering, sleep, and selected activities of daily living in the user'slife. Prototype schedules may be offered as guides for how thesesuggested activities can be incorporated into the user's life. The usermay periodically retake the survey, and based on the results, the itemsdiscussed above will be adjusted accordingly.

The Nutrition category is calculated from both data input by the userand sensed by sensor device 10. The data input by the user comprises thetime and duration of breakfast, lunch, dinner and any snacks, and thefoods eaten, the supplements such as vitamins that are taken, and thewater and other liquids consumed during a relevant, pre-selected timeperiod. Based upon this data and on stored data relating to knownproperties of various foods, central monitoring unit 30 calculates wellknown nutritional food values such as calories and amounts of proteins,fats, carbohydrates, vitamins, etc., consumed.

The Nutrition Health Index piston level is preferably determined withrespect to the following suggested healthy daily routine: eat at leastthree meals; eat a varied diet consisting of 6-11 servings of bread,pasta, cereal, and rice, 2-4 servings fruit, 3-5 servings of vegetables,2-3 servings of fish, meat, poultry, dry beans, eggs, and nuts, and 2-3servings of milk, yogurt and cheese; and drink 8 or more 8 ounce glassesof water. This routine may be adjusted based on information about theuser, such as sex, age, height and/or weight. Certain nutritionaltargets may also be set by the user or for the user, relating to dailycalories, protein, fiber, fat, carbohydrates, and/or water consumptionand percentages of total consumption. Parameters utilized in thecalculation of the relevant piston level include the number of meals perday, the number of glasses of water, and the types and amounts of foodeaten each day as input by the user.

Nutritional information is presented to the user through nutrition webpage 160 as shown in FIG. 6. The preferred nutritional web page 160includes nutritional fact charts 165 and 170 which illustrate actual andtarget nutritional facts, respectively as pie charts, and nutritionalintake charts 175 and 180 which show total actual nutritional intake andtarget nutritional intake, respectively as pie charts. Nutritional factcharts 165 and 170 preferably show a percentage breakdown of items suchas carbohydrates, protein and fat, and nutritional intake charts 175 and180 are preferably broken down to show components such as total andtarget calories, fat, carbohydrates, protein, and vitamins. Web page 160also includes meal and water consumption tracking 185 with time entries,hyperlinks 190 which allow the user to directly access nutrition-relatednews items and articles, suggestions for refining or improving dailyroutine with respect to nutrition and affiliate advertising elsewhere onthe network, and calendar 195 for choosing between views having variableand selectable time periods. The items shown at 190 may be selected andcustomized based on information learned about the individual in thesurvey and on their performance as measured by the Health Index.

The Activity Level category of Health Index 155 is designed to helpusers monitor how and when they move around during the day and utilizesboth data input by the user and data sensed by sensor device 10. Thedata input by the user may include details regarding the user's dailyactivities, for example the fact that the user worked at a desk from 8a.m. to 5 p.m. and then took an aerobics class from 6 p.m. to 7 p.m.Relevant data sensed by sensor device 10 may include heart rate,movement as sensed by a device such as an accelerometer, heat flow,respiration rate, calories burned, GSR and hydration level, which may bederived by sensor device 60 or central monitoring unit 30. Caloriesburned may be calculated in a variety of manners, including: themultiplication of the type of exercise input by the user by the durationof exercise input by the user; sensed motion multiplied by time ofmotion multiplied by a filter constant; or sensed heat flux multipliedby time multiplied by a filter constant.

The Activity Level Health Index piston level is preferably determinedwith respect to a suggested healthy daily routine that includes:exercising aerobically for a pre-set time period, preferably 20 minutes,or engaging in a vigorous lifestyle activity for a pre-set time period,preferably one hour, and burning at least a minimum target number ofcalories, preferably 205 calories, through the aerobic exercise and/orlifestyle activity. The minimum target number of calories may be setaccording to information about the user, such as sex, age, height and/orweight. Parameters utilized in the calculation of the relevant pistonlevel include the amount of time spent exercising aerobically orengaging in a vigorous lifestyle activity as input by the user and/orsensed by sensor device 10, and the number of calories burned abovepre-calculated energy expenditure parameters.

Information regarding the individual user's movement is presented to theuser through activity level web page 200 shown in FIG. 7, which mayinclude activity graph 205 in the form of a bar graph, for monitoringthe individual user's activities in one of three categories: high,medium and low intensity with respect to a pre-selected unit of time.Activity percentage chart 210, in the form or a pie chart, may also beprovided for showing the percentage of a pre-selected time period, suchas one day, that the user spent in each category. Activity level webpage 200 may also include calorie section 215 for displaying items suchas total calories burned, daily target calories burned, total caloricintake, and duration of aerobic activity. Finally, activity level webpage 200 may include at least one hyperlink 220 to allow a user todirectly access relevant news items and articles, suggestions forrefining or improving daily routine with respect to activity level andaffiliate advertising elsewhere on the network. Activity level web page200 may be viewed in a variety of formats, and may includeuser-selectable graphs and charts such as a bar graph, pie chart, orboth, as selectable by Activity level check boxes 225. Activity levelcalendar 230 is provided for selecting among views having variable andselectable time periods. The items shown at 220 may be selected andcustomized based on information learned about the individual in thesurvey and on their performance as measured by the Health Index.

The Mind Centering category of Health Index 155 is designed to helpusers monitor the parameters relating to time spent engaging in certainactivities which allow the body to achieve a state of profoundrelaxation while the mind becomes focused, and is based upon both datainput by the user and data sensed by the sensor device 10. Inparticular, a user may input the beginning and end times of relaxationactivities such as yoga or meditation. The quality of those activitiesas determined by the depth of a mind centering event can be measured bymonitoring parameters including skin temperature, heart rate,respiration rate, and heat flow as sensed by sensor device 10. Percentchange in GSR as derived either by sensor device 10 or centralmonitoring unit 30 may also be utilized.

The Mind Centering Health Index piston level is preferably calculatedwith respect to a suggested healthy daily routine that includesparticipating each day in an activity that allows the body to achieveprofound relaxation while the mind stays highly focused for at leastfifteen minutes. Parameters utilized in the calculation of the relevantpiston level include the amount of time spent in a mind centeringactivity, and the percent change in skin temperature, heart rate,respiration rate, heat flow or GSR as sensed by sensor device 10compared to a baseline which is an indication of the depth or quality ofthe mind centering activity.

Information regarding the time spent on self-reflection and relaxationis presented to the user through mind centering web page 250 shown inFIG. 8. For each mind centering activity, referred to as a session, thepreferred mind centering web page 250 includes the time spent during thesession, shown at 255, the target time, shown at 260, comparison section265 showing target and actual depth of mind centering, or focus, and ahistogram 270 that shows the overall level of stress derived from suchthings as skin temperature, heart rate, respiration rate, heat flowand/or GSR. In comparison section 265, the human figure outline showingtarget focus is solid, and the human figure outline showing actual focusranges from fuzzy to solid depending on the level of focus. Thepreferred mind centering web page may also include an indication of thetotal time spent on mind centering activities, shown at 275, hyperlinks280 which allow the user to directly access relevant news items andarticles, suggestions for refining or improving daily routine withrespect to mind centering and affiliate advertising, and a calendar 285for choosing among views having variable and selectable time periods.The items shown at 280 may be selected and customized based oninformation learned about the individual in the survey and on theirperformance as measured by the Health Index.

The Sleep category of Health Index 155 is designed to help users monitortheir sleep patterns and the quality of their sleep. It is intended tohelp users learn about the importance of sleep in their healthylifestyle and the relationship of sleep to circadian rhythms, being thenormal daily variations in body functions. The Sleep category is basedupon both data input by the user and data sensed by sensor device 10.The data input by the user for each relevant time interval includes thetimes the user went to sleep and woke up and a rating of the quality ofsleep. As noted in Table 2, the data from sensor device 10 that isrelevant includes skin temperature, heat flow, beat-to-beat heartvariability, heart rate, pulse rate, respiration rate, core temperature,galvanic skin response, EMG, EEG, EOG, blood pressure, and oxygenconsumption. Also relevant is ambient sound and body movement or motionas detected by a device such as an accelerometer. This data can then beused to calculate or derive sleep onset and wake time, sleepinterruptions, and the quality and depth of sleep.

The Sleep Health Index piston level is determined with respect to ahealthy daily routine including getting a minimum amount, preferablyeight hours, of sleep each night and having a predictable bed time andwake time. The specific parameters which determine the piston levelcalculation include the number of hours of sleep per night and the bedtime and wake time as sensed by sensor device 10 or as input by theuser, and the quality of the sleep as rated by the user or derived fromother data.

Information regarding sleep is presented to the user through sleep webpage 290 shown in FIG. 9. Sleep web page 290 includes a sleep durationindicator 295, based on either data from sensor device 10 or on datainput by the user, together with user sleep time indicator 300 and waketime indicator 305. A quality of sleep rating 310 input by the user mayalso be utilized and displayed. If more than a one day time interval isbeing displayed on sleep web page 290, then sleep duration indicator 295is calculated and displayed as a cumulative value, and sleep timeindicator 300, wake time indicator 305 and quality of sleep rating 310are calculated and illustrated as averages. Sleep web page 290 alsoincludes a user-selectable sleep graph 315 which calculates and displaysone sleep related parameter over a pre-selected time interval. Forillustrative purposes, FIG. 9 shows heat flow over a one-day period,which tends to be lower during sleeping hours and higher during wakinghours. From this information, a person's bio-rhythms can be derived.Sleep graph 315 may also include a graphical representation of data froman accelerometer incorporated in sensor device 10 which monitors themovement of the body. The sleep web page 290 may also include hyperlinks320 which allow the user to directly access sleep related news items andarticles, suggestions for refining or improving daily routine withrespect to sleep and affiliate advertising available elsewhere on thenetwork, and a sleep calendar 325 for choosing a relevant time interval.The items shown at 320 may be selected and customized based oninformation learned about the individual in the survey and on theirperformance as measured by the Health Index.

The Activities of Daily Living category of Health Index 155 is designedto help users monitor certain health and safety related activities andrisks and is based entirely on data input by the user. The Activities ofDaily Living category is divided into four sub-categories: personalhygiene, which allows the user to monitor activities such as brushingand flossing his or her teeth and showering; health maintenance, thattracks whether the user is taking prescribed medication or supplementsand allows the user to monitor tobacco and alcohol consumption andautomobile safety such as seat belt use; personal time, that allows theuser to monitor time spent socially with family and friends, leisure,and mind centering activities; and responsibilities, that allows theuser to monitor certain work and financial activities such as payingbills and household chores.

The Activities of Daily Living Health Index piston level is preferablydetermined with respect to the healthy daily routine described below.With respect to personal hygiene, the routine requires that the usersshower or bathe each day, brush and floss teeth each day, and maintainregular bowel habits. With respect to health maintenance, the routinerequires that the user take medications and vitamins and/or supplements,use a seat belt, refrain from smoking, drink moderately, and monitorhealth each day with the Health Manager. With respect to personal time,the routine requires the users to spend at least one hour of qualitytime each day with family and/or friends, restrict work time to amaximum of nine hours a day, spend some time on a leisure or playactivity each day, and engage in a mind stimulating activity. Withrespect to responsibilities, the routine requires the users to dohousehold chores, pay bills, be on time for work, and keep appointments.The piston level is calculated based on the degree to which the usercompletes a list of daily activities as determined by information inputby the user.

Information relating to these activities is presented to the userthrough daily activities web page 330 shown in FIG. 10. In preferreddaily activities web page 330, activities chart 335, selectable for oneor more of the sub-categories, shows whether the user has done what isrequired by the daily routine. A colored or shaded box indicates thatthe user has done the required activity, and an empty, non-colored orshaded box indicates that the user has not done the activity. Activitieschart 335 can be created and viewed in selectable time intervals. Forillustrative purposes, FIG. 10 shows the personal hygiene and personaltime sub-categories for a particular week. In addition, daily activitiesweb page 330 may include daily activity hyperlinks 340 which allow theuser to directly access relevant news items and articles, suggestionsfor improving or refining daily routine with respect to activities ofdaily living and affiliate advertising, and a daily activities calendar345 for selecting a relevant time interval. The items shown at 340 maybe selected and customized based on information learned about theindividual in the survey and on their performance as measured by theHealth Index.

The How You Feel category of Health Index 155 is designed to allow usersto monitor their perception of how they felt on a particular day, and isbased on information, essentially a subjective rating, that is inputdirectly by the user. A user provides a rating, preferably on a scale of1 to 5, with respect to the following nine subject areas: mentalsharpness; emotional and psychological well being; energy level; abilityto cope with life stresses; appearance; physical well being;self-control; motivation; and comfort in relating to others. Thoseratings are averaged and used to calculate the relevant piston level.

Referring to FIG. 11, Health Index web page 350 is shown. Health Indexweb page 350 enables users to view the performance of their Health Indexover a user selectable time interval including any number of consecutiveor non-consecutive days. Using Health Index selector buttons 360, theuser can select to view the Health Index piston levels for one category,or can view a side-by-side comparison of the Health Index piston levelsfor two or more categories. For example, a user might want to just turnon Sleep to see if their overall sleep rating improved over the previousmonth, much in the same way they view the performance of their favoritestock. Alternatively, Sleep and Activity Level might be simultaneouslydisplayed in order to compare and evaluate Sleep ratings withcorresponding Activity Level ratings to determine if any day-to-daycorrelations exist. Nutrition ratings might be displayed with How YouFeel for a pre-selected time interval to determine if any correlationexists between daily eating habits and how they felt during thatinterval. For illustrative purposes, FIG. 11 illustrates a comparison ofSleep and Activity Level piston levels for the week of June 10 throughJune 16. Health Index web page 350 also includes tracking calculator 365that displays access information and statistics such as the total numberof days the user has logged in and used the Health Manager, thepercentage of days the user has used the Health Manager since becoming asubscriber, and percentage of time the user has used the sensor device10 to gather data.

Referring again to FIG. 5, opening Health Manager web page 150 mayinclude a plurality of user selectable category summaries 156 a through156 f, one corresponding to each of the Health Index 155 categories.Each category summary 156 a through 156 f presents a pre-selectedfiltered subset of the data associated with the corresponding category.Nutrition category summary 156 a displays daily target and actualcaloric intake. Activity Level category summary 156 b displays dailytarget and actual calories burned. Mind Centering category summary 156 cdisplays target and actual depth of mind centering or focus. Sleepcategory summary 156 d displays target sleep, actual sleep, and a sleepquality rating. Daily Activities category summary 156 e displays atarget and actual score based on the percentage of suggested dailyactivities that are completed. The How You Feel category summary 156 fshows a target and actual rating for the day.

Opening Health Manager web page 150 also may include Daily Dose section157 which provides, on a daily time interval basis, information to theuser, including, but not limited to, hyperlinks to news items andarticles, commentary and reminders to the user based on tendencies, suchas poor nutritional habits, determined from the initial survey. Thecommentary for Daily Dose 157 may, for example, be a factual statementthat drinking 8 glasses of water a day can reduce the risk of coloncancer by as much as 32%, accompanied by a suggestion to keep a cup ofwater by your computer or on your desk at work and refill often. OpeningHealth Manager web page 150 also may include a Problem Solver section158 that actively evaluates the user's performance in each of thecategories of Health Index 155 and presents suggestions for improvement.For example, if the system detects that a user's Sleep levels have beenlow, which suggest that the user has been having trouble sleeping,Problem Solver 158 can provide suggestions for way to improve sleep.Problem Solver 158 also may include the capability of user questionsregarding improvements in performance. Opening Health Manager web page150 may also include a Daily Data section 159 that launches an inputdialog box. The input dialog box facilitates input by the user of thevarious data required by the Health Manager. As is known in the art,data entry may be in the form of selection from pre-defined lists orgeneral free form text input. Finally, opening Health Manager web page150 may include Body Stats section 161 which may provide informationregarding the user's height, weight, body measurements, body mass indexor BMI, and vital signs such as heart rate, blood pressure or any of theidentified physiological parameters.

Referring to FIGS. 12-17, a specific embodiment of sensor device 10 isshown which is in the form of an armband adapted to be worn by anindividual on his or her upper arm, between the shoulder and the elbow.The specific embodiment of sensor device 10 shown in FIGS. 12-17 will,for convenience, be referred to as armband sensor device 400. Armbandsensor device 400 includes computer housing 405, flexible wing body 410,and, as shown in FIG. 17, elastic strap 415. Computer housing 405 andflexible wing body 410 are preferably made of a flexible urethanematerial or an elastomeric material such as rubber or a rubber-siliconeblend by a molding process. Flexible wing body 410 includes first andsecond wings 418 each having a thru-hole 420 located near the ends 425thereof. First and second wings 418 are adapted to wrap around a portionof the wearer's upper arm.

Elastic strap 415 is used to removably affix armband sensor device 400to the individual's upper arm. As seen in FIG. 17, bottom surface 426 ofelastic strap 415 is provided with Velcro loops 416 along a portionthereof. Each end 427 of elastic strap 415 is provided with Velcro hookpatch 428 on bottom surface 426 and pull tab 429 on top surface 430. Aportion of each pull tab 429 extends beyond the edge of each end 427.

In order to wear armband sensor device 400, a user inserts each end 427of elastic strap 415 into a respective thru-hole 420 of flexible wingbody 410. The user then places his arm through the loop created byelastic strap 415, flexible wing body 410 and computer housing 405. Bypulling each pull tab 429 and engaging Velcro hook patches 428 withVelcro loops 416 at a desired position along bottom surface 426 ofelastic strap 415, the user can adjust elastic strap 415 to fitcomfortably. Since Velcro hook patches 428 can be engaged with Velcroloops 416 at almost any position along bottom surface 426, armbandsensor device 400 can be adjusted to fit arms of various sizes. Also,elastic strap 415 may be provided in various lengths to accommodate awider range of arm sizes. As will be apparent to one of skill in theart, other means of fastening and adjusting the size of elastic strapmay be used, including, but not limited to, snaps, buttons, or buckles.It is also possible to use two elastic straps that fasten by one ofseveral conventional means including Velcro, snaps, buttons, buckles orthe like, or merely a single elastic strap affixed to wings 418.

Alternatively, instead of providing thru-holes 420 in wings 418, loopshaving the shape of the letter D, not shown, may be attached to ends 425of wings 418 by one of several conventional means. For example, a pin,not shown, may be inserted through ends 425, wherein the pin engageseach end of each loop. In this configuration, the D-shaped loops wouldserve as connecting points for elastic strap 415, effectively creating athru-hole between each end 425 of each wing 418 and each loop.

As shown in FIG. 18, which is an exploded view of armband sensor device400, computer housing 405 includes a top portion 435 and a bottomportion 440. Contained within computer housing 405 are printed circuitboard or PCB 445, rechargeable battery 450, preferably a lithium ionbattery, and vibrating motor 455 for providing tactile feedback to thewearer, such as those used in pagers, suitable examples of which are theModel 12342 and 12343 motors sold by MG Motors Ltd. of the UnitedKingdom.

Top portion 435 and bottom portion 440 of computer housing 405 sealinglymate along groove 436 into which O-ring 437 is fit, and may be affixedto one another by screws, not shown, which pass through screw holes 438a and stiffeners 438 b of bottom portion 440 and apertures 439 in PCB445 and into threaded receiving stiffeners 451 of top portion 435.Alternately, top portion 435 and bottom portion 440 may be snap fittogether or affixed to one another with an adhesive. Preferably, theassembled computer housing 405 is sufficiently water resistant to permitarmband sensor device 400 to be worn while swimming without adverselyaffecting the performance thereof.

As can be seen in FIG. 13, bottom portion 440 includes, on a bottom sidethereof, a raised platform 430. Affixed to raised platform 430 is heatflow or flux sensor 460, a suitable example of which is the micro-foilheat flux sensor sold by RdF Corporation of Hudson, N.H. Heat fluxsensor 460 functions as a self-generating thermopile transducer, andpreferably includes a carrier made of a polyamide film. Bottom portion440 may include on a top side thereof, that is on a side opposite theside to which heat flux sensor 460 is affixed, a heat sink, not shown,made of a suitable metallic material such as aluminum. Also affixed toraised platform 430 are GSR sensors 465, preferably comprisingelectrodes formed of a material such as conductive carbonized rubber,gold or stainless steel. Although two GSR sensors 465 are shown in FIG.13, it will be appreciated by one of skill in the art that the number ofGSR sensors 465 and the placement thereof on raised platform 430 canvary as long as the individual GSR sensors 465, i.e., the electrodes,are electrically isolated from one another. By being affixed to raisedplatform 430, heat flux sensor 460 and GSR sensors 465 are adapted to bein contact with the wearer's skin when armband sensor device 400 isworn. Bottom portion 440 of computer housing 405 may also be providedwith a removable and replaceable soft foam fabric pad, not shown, on aportion of the surface thereof that does not include raised platform 430and screw holes 438 a. The soft foam fabric is intended to contact thewearer's skin and make armband sensor device 400 more comfortable towear.

Electrical coupling between heat flux sensor 460, GSR sensors 465, andPCB 445 may be accomplished in one of various known methods. Forexample, suitable wiring, not shown, may be molded into bottom portion440 of computer housing 405 and then electrically connected, such as bysoldering, to appropriate input locations on PCB 445 and to heat fluxsensor 460 and GSR sensors 465. Alternatively, rather than moldingwiring into bottom portion 440, thru-holes may be provided in bottomportion 440 through which appropriate wiring may pass. The thru-holeswould preferably be provided with a water tight seal to maintain theintegrity of computer housing 405.

Rather than being affixed to raised platform 430 as shown in FIG. 13,one or both of heat flux sensor 460 and GSR sensors 465 may be affixedto the inner portion 466 of flexible wing body 410 on either or both ofwings 418 so as to be in contact with the wearer's skin when armbandsensor device 400 is worn. In such a configuration, electrical couplingbetween heat flux sensor 460 and GSR sensors 465, whichever the case maybe, and the PCB 445 may be accomplished through suitable wiring, notshown, molded into flexible wing body 410 that passes through one ormore thru-holes in computer housing 405 and that is electricallyconnected, such as by soldering, to appropriate input locations on PCB445. Again, the thru-holes would preferably be provided with a watertight seal to maintain the integrity of computer housing 405.Alternatively, rather than providing thru-holes in computer housing 405through which the wiring passes, the wiring may be captured in computerhousing 405 during an overmolding process, described below, andultimately soldered to appropriate input locations on PCB 445.

As shown in FIGS. 12, 16, 17 and 18, computer housing 405 includes abutton 470 that is coupled to and adapted to activate a momentary switch585 on PCB 445. Button 470 may be used to activate armband sensor device400 for use, to mark the time an event occurred or to request systemstatus information such as battery level and memory capacity. Whenbutton 470 is depressed, momentary switch 585 closes a circuit and asignal is sent to processing unit 490 on PCB 445. Depending on the timeinterval for which button 470 is depressed, the generated signaltriggers one of the events just described. Computer housing 405 alsoincludes LEDs 475, which may be used to indicate battery level or memorycapacity or to provide visual feedback to the wearer. Rather than LEDs475, computer housing 405 may also include a liquid crystal display orLCD to provide battery level, memory capacity or visual feedbackinformation to the wearer. Battery level, memory capacity or feedbackinformation may also be given to the user tactily or audibly.

Armband sensor device 400 may be adapted to be activated for use, thatis collecting data, when either of GSR sensors 465 or heat flux sensor460 senses a particular condition that indicates that armband sensordevice 400 has been placed in contact with the user's skin. Also,armband sensor device 400 may be adapted to be activated for use whenone or more of heat flux sensor 460, GSR sensors 465, accelerometer 495or 550, or any other device in communication with armband sensor device400, alone or in combination, sense a particular condition or conditionsthat indicate that the armband sensor device 400 has been placed incontact with the user's skin for use. At other times, armband sensordevice 400 would be deactivated, thus preserving battery power.

Computer housing 405 is adapted to be coupled to a battery rechargerunit 480 shown in FIG. 19 for the purpose of recharging rechargeablebattery 450. Computer housing 405 includes recharger contacts 485, shownin FIGS. 12, 15, 16 and 17, that are coupled to rechargeable battery450. Recharger contacts 485 may be made of a material such as brass,gold or stainless steel, and are adapted to mate with and beelectrically coupled to electrical contacts, not shown, provided inbattery recharger unit 480 when armband sensor device 400 is placedtherein. The electrical contacts provided in battery recharger unit 480may be coupled to recharging circuit 481 a provided inside batteryrecharger unit 480. In this configuration, recharging circuit 481 wouldbe coupled to a wall outlet, such as by way of wiring including asuitable plug that is attached or is attachable to battery rechargerunit 480. Alternatively, electrical contacts 480 may be coupled towiring that is attached to or is attachable to battery recharger unit480 that in turn is coupled to recharging circuit 481 b external tobattery recharger unit 480. The wiring in this configuration would alsoinclude a plug, not shown, adapted to be plugged into a conventionalwall outlet.

Also provided inside battery recharger unit 480 is RF transceiver 483adapted to receive signals from and transmit signals to RF transceiver565 provided in computer housing 405 and shown in FIG. 20. RFtransceiver 483 is adapted to be coupled, for example by a suitablecable, to a serial port, such as an RS 232 port or a USB port, of adevice such as personal computer 35 shown in FIG. 1. Thus, data may beuploaded from and downloaded to armband sensor device 400 using RFtransceiver 483 and RF transceiver 565. It will be appreciated thatalthough RF transceivers 483 and 565 are shown in FIGS. 19 and 20, otherforms of wireless transceivers may be used, such as infraredtransceivers. Alternatively, computer housing 405 may be provided withadditional electrical contacts, not shown, that would be adapted to matewith and be electrically coupled to additional electrical contacts, notshown, provided in battery recharger unit 480 when armband sensor device400 is placed therein. The additional electrical contacts in thecomputer housing 405 would be coupled to the processing unit 490 and theadditional electrical contacts provided in battery recharger unit 480would be coupled to a suitable cable that in turn would be coupled to aserial port, such as an RS R32 port or a USB port, of a device such aspersonal computer 35. This configuration thus provides an alternatemethod for uploading of data from and downloading of data to armbandsensor device 400 using a physical connection.

FIG. 20 is a schematic diagram that shows the system architecture ofarmband sensor device 400, and in particular each of the components thatis either on or coupled to PCB 445.

As shown in FIG. 17, PCB 445 includes processing unit 490, which may bea microprocessor, a microcontroller, or any other processing device thatcan be adapted to perform the functionality described herein. Processingunit 490 is adapted to provide all of the functionality described inconnection with microprocessor 20 shown in FIG. 2. A suitable example ofprocessing unit 490 is the Dragonball EZ sold by Motorola, Inc. ofSchaumburg, Ill. PCB 445 also has thereon a two-axis accelerometer 495,a suitable example of which is the Model ADXL210 accelerometer sold byAnalog Devices, Inc. of Norwood, Mass. Two-axis accelerometer 495 ispreferably mounted on PCB 445 at an angle such that its sensing axes areoffset at an angle substantially equal to 45 degrees from thelongitudinal axis of PCB 445 and thus the longitudinal axis of thewearer's arm when armband sensor device 400 is worn. The longitudinalaxis of the wearer's arm refers to the axis defined by a straight linedrawn from the wearer's shoulder to the wearer's elbow. The outputsignals of two-axis accelerometer 495 are passed through buffers 500 andinput into analog to digital converter 505 that in turn is coupled toprocessing unit 490. GSR sensors 465 are coupled to amplifier 510 on PCB445. Amplifier 510 provides amplification and low pass filteringfunctionality, a suitable example of which is the Model AD8544 amplifiersold by Analog Devices, Inc. of Norwood, Mass. The amplified andfiltered signal output by amplifier 510 is input into amp/offset 515 toprovide further gain and to remove any bias voltage and intofilter/conditioning circuit 520, which in turn are each coupled toanalog to digital converter 505. Heat flux sensor 460 is coupled todifferential input amplifier 525, such as the Model INA amplifier soldby Burr-Brown Corporation of Tucson, Ariz., and the resulting amplifiedsignal is passed through filter circuit 530, buffer 535 and amplifier540 before being input to analog to digital converter 505. Amplifier 540is configured to provide further gain and low pass filtering, a suitableexample of which is the Model AD8544 amplifier sold by Analog Devices,Inc. of Norwood, Mass. PCB 445 also includes thereon a battery monitor545 that monitors the remaining power level of rechargeable battery 450.Battery monitor 545 preferably comprises a voltage divider with a lowpass filter to provide average battery voltage. When a user depressesbutton 470 in the manner adapted for requesting battery level,processing unit 490 checks the output of battery monitor 545 andprovides an indication thereof to the user, preferably through LEDs 475,but also possibly through vibrating motor 455 or ringer 575. An LCD mayalso be used.

PCB 445 may include three-axis accelerometer 550 instead of or inaddition to two-axis accelerometer 495. The three-axis accelerometeroutputs a signal to processing unit 490. A suitable example ofthree-axis accelerometer is the μPAM product sold by I.M. Systems, Inc.of Scottsdale, Ariz. Three-axis accelerometer 550 is preferably tiltedin the manner described with respect to two-axis accelerometer 495.

PCB 445 also includes RF receiver 555 that is coupled to processing unit490. RF receiver 555 may be used to receive signals that are output byanother device capable of wireless transmission, shown in FIG. 20 aswireless device 558, worn by or located near the individual wearingarmband sensor device 400. Located near as used herein means within thetransmission range of wireless device 558. For example, wireless device558 may be a chest mounted heart rate monitor such as the Tempo productsold by Polar Electro of Oulu, Finland. Using such a heart rate monitor,data indicative of the wearer's heart rate can be collected by armbandsensor device 400. Antenna 560 and RF transceiver 565 are coupled toprocessing unit 490 and are provided for purposes of uploading data tocentral monitoring unit 30 and receiving data downloaded from centralmonitoring unit 30. RF transceiver 565 and RF receiver 555 may, forexample, employ Bluetooth technology as the wireless transmissionprotocol. Also, other forms of wireless transmission may be used, suchas infrared transmission.

The fact that RF Transceiver 565 may be used for wirelessly uploadingdata from and wirelessly downloading data to armband sensor device 400is advantageous because it eliminates the need to remove armband sensordevice 400 to perform these functions, as would be required with aphysical connection. For example, if armband sensor device 400 was beingworn under the user's clothing, requiring removal of armband sensordevice 400 prior to uploading and/or downloading data increases userinconvenience. In addition, the wearing of armband sensor device 400 hasan effect on the user's skin and underlying blood vessels, which in turnmay effect any measurements being made with respect thereto. It may benecessary for a period of time during which armband sensor device 400 isworn by the user to elapse before a steady state is achieved andconsistent, accurate measurements can be made. By providing armbandsensor device 400 with wireless communications capability, data can beuploaded and downloaded without disturbing an established steady stateequilibrium condition. For example, programming data for processing unit490 that controls the sampling characteristics of armband sensor device400 can be downloaded to armband sensor device 400 without disturbingthe steady state equilibrium condition.

In addition, antenna 560 and RF transceiver 565 permit armband sensordevice 400 to communicate wirelessly with other devices capable ofwireless communication, i.e., transmit information to and receiveinformation from those devices. In embodiments where non-invasiveness isnot the goal, the devices may include, for example, devices that areimplanted in the body of the person using armband sensor device 400,such as an implantable heart pacemaker or an implantable insulindispensing device, for example the MiniMed® 2007 implantable insulinpump sold by MiniMed Inc. of Northridge, Calif., devices worn on thebody of the person using armband sensor device 400, or devices locatednear the person using armband sensor device 400 at any particular time,such as an electronic scale, a blood pressure monitor, a glucosemonitor, a cholesterol monitor or another armband sensor device 400.With this two-way wireless communication capability, armband sensordevice 400 may be adapted to transmit information that activates ordeactivates such a device for use or information that programs such adevice to behave in a particular way. For example, armband sensor device400 may be adapted to activate a piece of exercise equipment such as atreadmill and program it to operate with certain parameters that aredictated or desired by or optimal for the user of armband sensor device400. As another example, armband sensor device 400 may be adapted toadjust a computer controlled thermostat in a home based on the detectedskin temperature of the wearer or turn off a computer controlledlighting system, television or stereo when the wearer is determined tohave fallen asleep.

Vibrating motor 455 is coupled to processing unit 490 through vibratordriver 570 and provides tactile feedback to the wearer. Similarly,ringer 575, a suitable example of which is the Model SMT916A ringer soldby Projects Unlimited, Inc. of Dayton, Ohio, is coupled to processingunit 490 through ringer driver 580, a suitable example of which is theModel MMBTA14 CTI darlington transistor driver sold by Motorola, Inc. ofSchaumburg, Ill., and provides audible feedback to the wearer. Feedbackmay include, for example, celebratory, cautionary and other threshold orevent driven messages, such as when a wearer reaches a level of caloriesburned during a workout.

Also provided on PCB 445 and coupled to processing unit 490 is momentaryswitch 585. Momentary switch 585 is also coupled to button 470 foractivating momentary switch 585. LEDs 475, used to provide various typesof feedback information to the wearer, are coupled to processing unit490 through LED latch/driver 590.

Oscillator 595 is provided on PCB 445 and supplies the system clock toprocessing unit 490. Reset circuit 600, accessible and triggerablethrough a pin-hole in the side of computer housing 405, is coupled toprocessing unit 490 and enables processing unit 490 to be reset to astandard initial setting.

Rechargeable battery 450, which is the main power source for the armbandsensor device 400, is coupled to processing unit 490 through voltageregulator 605. Finally, memory functionality is provided for armbandsensor device 400 by SRAM 610, which stores data relating to the wearerof armband sensor device 400, and flash memory 615, which stores programand configuration data, provided on PCB 445. SRAM 610 and flash memory615 are coupled to processing unit 490 and each preferably have at least512 K of memory.

In manufacturing and assembling armband sensor device 400, top portion435 of computer housing 405 is preferably formed first, such as by aconventional molding process, and flexible wing body 410 is thenovermolded on top of top portion 435. That is, top portion 435 is placedinto an appropriately shaped mold, i.e., one that, when top portion 435is placed therein, has a remaining cavity shaped according to thedesired shape of flexible wing body 410, and flexible wing body 410 ismolded on top of top portion 435. As a result, flexible wing body 410and top portion 435 will merge or bond together, forming a single unit.Alternatively, top portion 435 of computer housing 405 and flexible wingbody 410 may be formed together, such as by molding in a single mold, toform a single unit. The single unit however formed may then be turnedover such that the underside of top portion 435 is facing upwards, andthe contents of computer housing 405 can be placed into top portion 435,and top portion 435 and bottom portion 440 can be affixed to oneanother. As still another alternative, flexible wing body 410 may beseparately formed, such as by a conventional molding process, andcomputer housing 405, and in particular top portion 435 of computerhousing 405, may be affixed to flexible wing body 410 by one of severalknown methods, such as by an adhesive, by snap-fitting, or by screwingthe two pieces together. Then, the remainder of computer housing 405would be assembled as described above. It will be appreciated thatrather than assembling the remainder of computer housing 405 after topportion 435 has been affixed to flexible wing body 410, the computerhousing 405 could be assembled first and then affixed to flexible wingbody 410.

Referring to FIG. 21, a block diagram of an alternate embodiment of thepresent invention is shown. This alternate embodiment includes standalone sensor device 700 which functions as an independent device,meaning that it is capable of collecting and/or generating the varioustypes of data described herein in connection with sensor device 10 andsensor device 400 and providing analytical status data to the userwithout interaction with a remotely located apparatus such as centralmonitoring unit 30. Stand alone sensor device 700 includes a processorthat is programmed and/or otherwise adapted to include the utilities andalgorithms necessary to create analytical status data from the dataindicative of various physiological and/or contextual parameters of theuser, the data derived therefrom, and the data input by the user, all ofwhich is stored in and accessed as needed from memory provided in standalone sensor device 700. Stand alone sensor device 700 may comprisesensor device 10 shown in FIGS. 1 and 2 that includes microprocessor 20and memory 22 or armband sensor device 400 shown in FIGS. 12-17 thatincludes processing unit 490 and SRAM 610.

As shown schematically in FIG. 21, data may be input into stand alonesensor device 700 in a number of ways. Stand alone sensor device 700 mayinclude one or more physiological sensors 705 as described herein forfacilitating the collection of data indicative of various physiologicalparameters of the user. Stand alone sensor device 700 may also includeone or more contextual sensors 710 as described herein for facilitatingthe collection of data indicative of various contextual parameters ofthe user. As indicated by reference number 715, stand alone sensordevice 700 may be adapted to enable the manual entry of data by theuser. For example, stand alone sensor device 700 may include a datainput button, such as a button 470 of armband sensor device 400, throughwhich a user could manually enter information such as informationrelating to various life activities of the user as described herein orinformation relating to the operation and/or control of stand alonesensor device 700, for example, the setting of reminders or alerts asdescribed herein. In this example, activation of button 470 may simplyrecord or time stamp that an event such as a meal has occurred, with thewearer needing to assign a meaning to that time stamp through data entryat a later time. Alternatively, activation of button 470 in certainsequences, such as one activation, two successive activations, threesuccessive activations, etc., can be preset to have different specificmeanings. A wearer would need to follow a menu or guide of such presetactivation sequences to input relevant data. Alternatively, stand alonesensor device 700 may include a more sophisticated means for manualentry of information such as a keypad, a touch screen, a microphone, ora remote control device, for example a remote control deviceincorporated into a wristwatch. In the case of a microphone, theprocessor of stand alone sensor device 700 would be provided with wellknown voice recognition software or the like for converting the inputspeech into usable data.

As indicated by reference numbers 720 and 725, information comprisingdata indicative of various physiological and/or contextual parametersand data derived therefrom may be input into stand alone sensor device700 through interaction with other devices. In addition, informationsuch as handshake data or data indicative of various physiologicaland/or contextual parameters and data derived therefrom may be outputfrom stand alone sensor device 700 to such other devices. According toone embodiment, the interaction is in the form of wireless communicationbetween stand alone sensor device 700 and another device capable ofwireless communication by way of a wireless transceiver provided instand alone sensor device 700, such as wireless transceiver 565 shownand described in connection with FIG. 20. The device-to-deviceinteraction may, as shown by reference number 720, be explicit, meaningthat the user of stand alone sensor device 700 has knowingly initiatedthe interaction. For example, a user may activate a button on a scale toupload data to stand alone sensor device 700. The device-to-deviceinteraction may also, as shown by reference number 725, be hidden,meaning that the user of stand alone sensor device 700 does notknowingly initiate the interaction. For example, a gym may have a sensorthat wirelessly transmits a signal to sensing device 700 when the userenters and leaves the gym to time stamp when the user began and ended aworkout.

As shown schematically in FIG. 21, information may be output ortransmitted from stand alone sensor device 700 in a number of ways. Suchinformation may include the data indicative of various physiologicalparameters and/or contextual parameters, the data derived therefrom, thedata manually input by the user, the analytical status data, or anycombination thereof. As shown by reference numbers 730, 735 and 740,information may be output or transmitted in an audible fashion such asby a series of tones or beeps or a recorded voice by a device such as aspeaker, in a visual fashion such as by one or more LEDs, or in atactile fashion such as by vibration. For example, stand alone sensordevice 700 may be adapted to output a tone or tones, light an LED orLEDs, or vibrate as a reminder for an event, such as a reminder to eator exercise at a particular time, or when a goal has been reached, suchas a target number of calories burned during a workout, or a conditionhas been sensed, such as ovulation. Alternatively, stand alone sensordevice 700 may be provided with a more sophisticated visual output meanssuch as an LCD similar to those found on commercially available cellphones, pagers and personal digital assistants. With an LCD or a similardevice and the expanded visual output capabilities it would provide,stand alone sensor device 700 may be adapted to output or transmit someor all of the information described in connection with FIGS. 5 through11 in the same or a similar format. For example, stand alone sensordevice 700 could provide analytical status data in the form of theHealth Index to the user. As a further alternative, stand alone sensordevice 700 may be coupled to computing device 750 such as a personalcomputer, a cell phone, a pager, a personal digital assistant, anotherstand alone sensor device 700 or any other device having a processor byeither wired connection 755 or wireless connection 760. For example,battery recharger unit 480 shown in FIG. 19 may be used to provide thewired connection 755 or wireless connection 760. In this configuration,the display of the computing device could be used to visually outputinformation from stand alone sensor device 700. It will be appreciatedthat since computing device 750 includes a sophisticated output meanssuch as an LCD, it may be used to output or transmit to the user some orall of the information described in connection with FIGS. 5 through 11,such as the Health Index, in the same or a similar format.

Also, computing device 750 may in turn be used to control other devices,such as the lights or thermostat in a home, based on data output bystand alone sensor device 700, such as the fact that the wearer hasfallen asleep or the fact that the wearer's skin temperature has reacheda certain level. In other words, stand alone sensor device 700, and inparticular its processor, may be adapted to cause a computing device 750to trigger an event upon detection of one or more physiological and/orcontextual conditions by stand alone sensor device 700. Alternatively,stand alone sensor device 700 may be adapted to cause a computing device750 to trigger an event based upon information received from anothercomputing device 750.

Stand alone sensor device 700 may be adapted to interact with andinfluence an interactive electronic media device, such as a video game,or non-interactive electronic media device, such as on a display devicesuch as a DVD or digital video disc player playing a digitally recordedmovie. For example, stand alone sensor device 700 may be adapted totransmit information relating to the physiological state of the wearerto the video game, which in turn adjusts the characteristics of thegame, such as the level of difficulty. As another example, stand alonesensor device 700 may be adapted to transmit information relating to thephysiological state of the wearer to the device displaying the digitallyrecorded movie which in turn adjusts the characteristics, such as theoutcome, of the movie.

Furthermore, stand alone sensor device 700 may include location sensingdevice 765, such as an ultrasonic or a radio-frequency identificationtag, for enabling a computing device 750 to detect the geographiclocation of stand alone sensor device 700, such as the location of standalone sensor device 700 within a defined space such as a building. Inone embodiment, a location indication causes computing device 750 totrigger an event, such as lowering the temperature in a roomcorresponding to the indicated location, preferably based on thedetection by stand alone sensor device 700 of one or more physiologicalconditions of the wearer, such as skin temperature. In anotherembodiment, the location indication causes computing device 750 totrigger an event, such as lowering the temperature in a roomcorresponding to the indicated location, if stand alone sensor device700 detects one or more physiological conditions, such as a skintemperature of the wearer being above a certain level. In addition, theinput means of the computing device, such as the mouse and keyboard of apersonal computer, the keypad of a cell phone or pager, or the touchscreen of a personal digital assistant, may be used to manually inputinformation into stand alone sensor device 700.

The different modes of output may be used in combination to providedifferent types and levels of information to a user. For example, standalone sensor device 700 could be worn by an individual while exercisingand an LED or a tone can be used to signal that a goal of a certainnumber of calories burned has been reached. The user could then transmitadditional data wirelessly from stand alone sensor device 700 to acomputing device 750 such as a cell phone after he or she is finishedexercising to view data such as heart rate and/or respiration rate overtime.

As a further alternative embodiment of the present invention, ratherthan the processor provided in stand alone sensor device 700 beingprogrammed and/or otherwise adapted to generate the derived data and toinclude the utilities and algorithms necessary to create analyticalstatus data, computing device 750 could be so programmed. In thisembodiment, stand alone sensor device 700 collects and/or generates thedata indicative of various physiological and/or contextual parameters ofthe user, the data manually input by the user, and/or data input as aresult of device-to-device interaction shown at 720 and 725, all ofwhich is stored in the memory provided in stand alone sensor device 700.This data is then periodically uploaded to computing device 750 which inturn generates derived data and/or analytical status data.Alternatively, the processor of stand alone sensor device 700 could beprogrammed to generate the derived data with computing device 750 beingprogrammed and/or otherwise adapted to include the utilities andalgorithms necessary to create analytical status data based on dataindicative of one or more physiological and/or contextual parameters,data derived therefrom, data manually input by the user and/or datainput as a result of device-to-device interaction shown at 720 and 725uploaded from stand alone sensor device 700. As still a furtheralternative, the processor of stand alone sensor device 700 could beprogrammed and/or otherwise adapted to include the utilities andalgorithms necessary to create analytical status data based on dataindicative of one or more physiological and/or contextual parameters,data derived therefrom, data manually input by the user and/or datainput as a result of device-to-device interaction shown at 720 and 725uploaded from stand alone sensor device 700 with computing device 750being programmed to generate the derived data. In either alternative,any or all of the data indicative of physiological and/or contextualparameters of the user, the data derived therefrom, the data manuallyinput by the user, the data input as a result of device-to-deviceinteraction shown at 720 and 725 and the analytical status data may thenbe viewed by the user using the output means of the programmed computingdevice 750 or another computing device 750 to which the data isdownloaded. In the latter alternative, everything but the analyticalstatus data may also be output by stand alone sensor device 700 asdescribed herein.

Computing device 750 in these alternative embodiments may be connectedto an electronic network, such as the Internet, to enable it tocommunicate with central monitoring unit 30 or the like. The programmingof computing device 750 that enables it to generate the derived dataand/or the analytical status data may, with such a configuration, bemodified or replaced by downloading the relevant data to computingdevice 750 over the electronic network.

As still a further alternative embodiment, computing device 750 may beprovided with a custom written plug-in adapted to provide data displayfunctionality through use of a well known browser program. In thisembodiment, stand alone sensor device 700 collects and/or generates thedata indicative of various physiological and/or contextual parameters ofthe user, the derived data, the data input by the user, data input as aresult of device-to-device interaction shown at 720 and 725, and/oranalytical status data based thereon and uploads this data to computingdevice 750. The plug-in provided in computing device 750 then generatesappropriate display pages based on the data which may be viewed by theuser using the browser provided with computing device 750. The plug-inmay be modified/updated from a source such as central monitoring unit 30over an electronic network such as the Internet.

Referring to FIGS. 22-26, an alternate embodiment of a sensor device isshown at 800. Sensor device 800 may be a specific embodiment of eithersensor device 10 described in connection with FIGS. 1-11 or stand alonesensor device 700 described in connection with FIG. 21. Sensor device800 includes housing 805 affixed to flexible section 810, which issimilar to flexible wing body 410 shown in FIGS. 12-17. Flexible section810 is adapted to engage, such as by wrapping around or conforming to,at least a portion of the human body, such as the upper arm, to enablesensor device 800, in combination with a removable strap 811 insertedthrough slots 812 provided in flexible section 810, to be worn on thebody. Preferably, flexible section 810 is made of a material having adurometer of between 75 and 85 Shore A. Flexible section 810 may take ona variety of shapes and may be made of a cloth material, a flexibleplastic film, or an elastic material having an adhesive similar instructure to a Band-Aid® disposable adhesive bandage. In the embodimentshown in FIGS. 22-26, housing 805 is permanently affixed to flexiblesection 810, such as by an over molding or co-molding process, throughthe use of an adhesive material, or by a fastening mechanism such as oneor more screws. Housing 805 includes top portion 815 affixed to bottomportion 820 by any known means, including, for example, an adhesivematerial, screws, snap fittings, sonic welding, or thermal welding.According to a preferred embodiment, a watertight seal is providedbetween top portion 815 and bottom portion 820. Such a water-tight sealis provided when sonic welding or thermal welding is used.Alternatively, an O-ring could be provided between top portion 815 andbottom portion 820 to create the water-tight seal.

As can be seen most readily in FIGS. 23, 24 and 26, affixed to bottomportion 820 of housing 805 are GSR sensors 825. GSR sensors 825 measurethe conductivity of the skin between two points and may compriseelectrodes formed of a material such as stainless steel, gold or aconductive carbonized rubber. Preferably, GSR sensors 825 have anoblong, curved shape as shown in FIG. 23, much like a kidney bean shape,that allows some portion of GSR sensors 825 to maintain contact with thebody even if sensor device 800 is rocking or otherwise moving whilebeing worn. Most preferably, GSR sensors 825 include raised bumps 830,or some other three-dimensional textured surface, along the surfacethereof to perturb the skin and push between hairs to ensure goodcontact with the skin. In addition, raised bumps 830 provide channelsfor the movement of sweat underneath sensor device 800, rather thantrapping sweat, no matter the orientation of sensor device with respectto the body. Also affixed to bottom portion 820 are heat flux skininterface component 835 and skin temperature skin interface component840, each comprising a plate made of a thermally conductive materialsuch as stainless steel. Preferably, heat flux skin interface component835 and skin temperature skin interface component 840 are made of amaterial having thermal conduction properties of at least 12.9 W/mK,such as 304 stainless steel. Preferably, GSR sensors 825 are spaced atleast 0.44 inches apart from one another, and at least 0.09 inches apartfrom heat flux skin interface component 835 and skin temperature skininterface component 840. GSR sensors 825, heat flux skin interfacecomponent 835 and skin temperature skin interface component 840 areadapted to be in contact with the wearer's skin when sensor device 800is worn, and facilitate the measurement of GSR, heat flux from the bodyand skin temperature data. As can be seen most readily in FIGS. 22, 24and 26, affixed to top portion 815 of housing 805 are heat flux ambientinterface component 845 and ambient temperature interface component 850,which also are made of a thermally conductive material such as stainlesssteel, preferably a material having thermal conduction properties of atleast 12.9 W/mK, such as 304 stainless steel. Heat flux ambientinterface component 845 and ambient temperature interface component 850facilitate the measurement of heat flux from the body and ambienttemperature, respectively, by providing a thermal interface to thesurrounding environment. To further enhance the measurement of theseparameters, holes 855 are provided in flexible section 810 to exposeheat flux ambient interface component 845 and ambient temperatureinterface component 850 to the ambient air. Preferably, holes 855 aresized so that flexible section 810 occludes as little skin as possiblein the regions surrounding heat flux ambient interface component 845 andambient temperature interface component 850 so as to allow air flowingoff of the skin of the wearer to pass these components.

GSR Sensors 825, heat flux, skin interface component 835, skintemperature skin interface component 840, or any other sensing componentthat comes into contact with the skin may be provided with a pluralityof microneedles for, among other things, enhancing electrical contactwith the skin and providing real time access to interstitial fluid inand below the epidermis, which access may be used to measure variousparameters such as pH level of the skin through electrochemical,impedance based or other well known methods. Microneedles enhanceelectrical contact by penetrating the stratum corneum of the skin toreach the epidermis. Such microneedles are well known in the art and maybe made of a metal or plastic material. Prior art microneedles aredescribed in, for example, U.S. Pat. No. 6,312,612 owned by the Procterand Gamble Company. Based on the particular application, the number,density, length, width at the point or base, distribution and spacing ofthe microneedles will vary.

Referring to FIG. 26, which is a cross-section taken along lines A-A inFIG. 22, the internal components of sensor device 800, housed withinhousing 805, are shown. Printed circuit board or PCB 860 is affixed totop portion 815 of housing 805 and receives and supports the electroniccomponents provided inside housing 805. Affixed to a bottom side of PCB860 and electronically coupled to GSR sensors 825 are contacts 865,which preferably comprise gold plated contact pins such as the Pogo®contacts available from Everett Charles Technologies in Pomona, Calif.Also affixed to the bottom side of PCB 860 is skin temperaturethermistor 870, a suitable example of which is the model 100 K6D280thermistor manufactured by BetaTherm Corporation in Shrewsbury, Mass.Skin temperature thermistor 870 is, according to a preferred embodiment,thermally coupled to skin temperature skin interface component 840 by athermally conductive interface material 875. Thermally conductiveinterface material 875 may be any type of thermally conductive interfaceknown in the art, including, for example, thermally conductive gapfillers, thermally conductive phase change interface materials,thermally conductive tapes, thermally conductive cure-in-place compoundsor epoxies, and thermal greases. Suitable thermally conductive interfacematerials include a boron nitride filled expandedpolytetrafluoroethylene matrix sold under the trademark PolarChip CP8000by W. L. Gore & Associates, Inc. and a boron nitride and alumina filledsilicone elastomer on an adhesive backed 5 mil. (0.013 cm) thickaluminum foil carrier called A574, which is available from the Chomericsdivision of Parker Hannefin Corp. located in Woburn, Mass. Provided ontop of PCB 860 is near-body ambient temperature thermistor 880, asuitable example of which is the model NTHS040ZN0IN100 KJ thermistormanufactured by Vishay Intertechnology, Inc. in Malvern, Pa. Near-bodyambient temperature thermistor 880 is thermally coupled to ambienttemperature interface component 850 by thermally conductive interfacematerial 875.

Still referring to FIG. 26, a preferred embodiment of sensor device 800includes a particular embodiment of an apparatus for measuring heat fluxbetween a living body and the ambient environment described inco-pending application Ser. No. 09/822,890, the disclosure of which isincorporated herein by reference in its entirety. Specifically, heatconduit 885 is provided within housing 805. As used herein, the termheat conduit refers to one or more heat conductors which are adapted tosingly or jointly transfer heat from one location to another, such as aconductor made of stainless steel. Heat conduit 885 is thermally coupledto heat flux skin interface component 835 by thermally conductiveinterface material 875. Provided on the bottom side of PCB 860 is afirst heat flux thermistor 890A, and provided on the top side of PCB 860is a second heat flux thermistor 890B. PCB 860 acts as a base member forsupporting these components. It will be appreciated that a base memberseparate and apart from PCB 860 may be substituted therefor as analternative configuration. A suitable example of both heat fluxthermistors 890A and 890B is the Heat flux Thermistor 890A and 890B aresoldered to pads provided on PCB 860. The second heat flux thermistor890B is thermally coupled to heat flux ambient interface 845 bythermally conductive interface material 875. As is well-known in theart, PCB 860 is made of a rigid or flexible material, such as afiberglass, having a preselected, known thermal resistance orresistivity K. The heat flux off of the body of the wearer can bedetermined by measuring a first voltage V1 with heat flux thermistor890A and a second voltage V2 with heat flux thermistor 890B. Thesevoltages are then electrically differenced, such as by using adifferential amplifier, to provide a voltage value that, as is wellknown in the art, can be used to calculate the temperature difference(T2−T1) between the top and bottom sides of PCB 860. Heat flux can thenbe calculated according to the following formula:Heat Flux=K(T2−T1)The combination of PCB 860 and heat flux thermistors 890A and 890B arethus a form of a heat flux sensor One advantage of the configuration ofthe apparatus for measuring heat flux shown in FIG. 26 is that, due tothe vertical orientation of the components, assembly of the apparatusfor measuring heat flux, and thus sensor device 800 as a whole, issimplified. Also adding to the simplicity is the fact that thermallyconductive interface materials that include a thin adhesive layer on oneor both sides may be used for thermally conductive interface materials875, enabling components to be adhered to one another. In addition,thermistors 890A and 890B are relatively inexpensive components, ascompared to an integral heat flux sensor such as those commerciallyavailable from RdF Corporation of Hudson, N.H., thereby reducing thecost of sensor device 800. Although heat flux thermistors 890A and 890Bare described as being provided on PCB 860 in the embodiment shown inFIG. 26, it will be appreciated that any piece of material having aknown resistivity K may be used. Furthermore, other temperaturemeasuring devices known in the art, such as a thermocouple orthermopile, may be substituted for heat flux thermistors 890A and 890B.As a further alternative, heat conduit 885 may be omitted such thatthermal communication between heat flux thermistor 890A and heat fluxskin interface component 835 is provided by one or more pieces ofthermally conductive interface material 875. As still a furtheralternative, heat flux skin interface component 835 may be omitted suchthat thermal communication between heat flux thermistor 890A and theskin is provided by either or both of heat conduit 885 and one or morepieces of thermally conductive interface material 875. In any of theembodiments described herein, the combination of one or more of heatconduit 885, one or more pieces of thermally conductive interfacematerial 875, and heat flux skin interface component 835 act as athermal energy communicator for placing heat flux thermistor 890A inthermal communication with the body of the wearer of sensor device 800.

FIG. 27 is a schematic diagram that shows an embodiment of the systemarchitecture of sensor device 800, and in particular each of thecomponents that is either provided on or coupled to PCB 860.

As shown in FIG. 27, PCB 860 includes processing unit 900, which may bea microprocessor, a microcontroller, or any other processing device thatcan be adapted to perform the functionality described herein, inparticular the functionality described in connection with microprocessor20 shown in FIG. 2, processing unit 490 shown in FIG. 20, or stand alonesensor device 700 shown in FIG. 21. A suitable example of processingunit 900 is the Dragonball EZ sold by Motorola, Inc. of Schaumburg, Ill.Also provided on PCB 860 is accelerometer 905, which may be either atwo-axis or a three-axis accelerometer. A suitable example of a two-axisaccelerometer is the Model ADXL202 accelerometer sold by Analog Devices,Inc. of Norwood, Mass., and a suitable example of a three-axisaccelerometer is the model ACH-04-08-05 accelerator sold by MeasurementSpecialties Incorporated in Norristown, Pa. The output signals ofaccelerometer 905 are passed through buffers 910 and input analog todigital, referred to as A/D, converter 915 that in turn is coupled toprocessing unit 900. GSR sensors 825 are coupled to A/D converter 915through current loop 920, low pass filter 925, and amplifier 930.Current loop 920 comprises an opamp and a plurality of resistors, andapplies a small, fixed current between the two GSR sensors 825 andmeasures the voltage across them. The measured voltage is directlyproportional to the resistance of the skin in contact with theelectrodes. Similarly, heat flux thermistors 890A and 890B are coupledto A/D converter 915 and processing unit 900, where the heat fluxcalculations are performed, through low pass filter 935 and amplifier940.

Battery monitor 945, preferably comprising a voltage divider with lowpass filter to provide average battery voltage, monitors the remainingpower level of rechargeable battery 950. Rechargeable battery 950 ispreferably a Lilon/LiPolymer 3.7 V Cell. Rechargeable battery 950, whichis the main power source for sensor device 800, is coupled to processingunit 900 through voltage regulator 955. Rechargeable battery 950 may berecharged either using recharger 960 or USB cable 965, both of which maybe coupled to sensor device 800 through USB interface 970. Preferably,USB interface 970 is hermetically sealable, such as with a removableplastic or rubber plug, to protect the contacts of USB interface 970when not in use.

PCB 860 further includes skin temperature thermistor 870 for sensing thetemperature of the skin of the wearer of sensor device 800, andnear-body ambient temperature thermistor 880 for sensing the ambienttemperature in the area near the body of the wearer of sensor device800. Each of these components is biased and coupled to processing unit900 through A/D converter 915.

According to a specific embodiment of sensor device 800, PCB 860 mayinclude one or both of an ambient light sensor and an ambient soundsensor, shown at 975 in FIG. 27, coupled to A/D converter 915. Theambient light sensor and ambient sound sensor may be adapted to merelysense the presence or absence of ambient light or sound, the state wherea threshold ambient light or sound level has been exceeded, or a readingreflecting the actual level of ambient light or sound. A suitableexample of an ambient sound sensor is the WM-60A Condenser MicrophoneCartridge sold by Matsushita Electric Corporation of America located inSecaucus, N.J., and suitable examples of an ambient light sensor are theOptek OPR5500 phototransistor and the Optek OPR5910 photodiode sold byOptek Technology, Inc. located in Carrollton, Tex. In addition, PCB 860may include ECG sensor 980, including two or more electrodes, formeasuring the heart rate of the wearer, and impedance sensor 985, alsoincluding a plurality of electrodes, for measuring the impedance of theskin of the wearer. Impedance sensor 985 may also be an EMG sensor whichgives an indication of the muscular activity of the wearer. Theelectrodes forming part of ECG sensor 980 or impedance sensor 985 may bededicated electrodes for such sensors, or may be the electrodes from GSRsensors 825 multiplexed for appropriate measurements. ECG sensor 980 andimpedance sensor 985 are each coupled to A/D converter 915.

PCB 860 further includes RF transceiver 990, coupled to processing unit900, and antenna 995 for wirelessly transmitting and receiving data toand from wireless devices in proximity to sensor device 800. RFtransceiver 990 and antenna 995 may be used for transmitting andreceiving data to and from a device such as a treadmill being used by awearer of sensor device 800 or a heart rate monitor worn by the wearerof sensor device 800, or to upload and download data to and from acomputing device such as a PDA or a PC. In addition, RF transceiver 990and antenna 995 may be used to transmit information to a feedback devicesuch as a bone conductivity microphone worn by a fireman to let thefireman know if a condition that may threaten the fireman's safety, suchas hydration level or fatigue level, has been sensed by sensor device800. As described in detail in connection with FIG. 21, stand alongsensor device 700 may be coupled to computing device 750 to enable datato be communicated therebetween. Thus, as a further alternative, RFtransceiver 990 and antenna 995 may be used to couple sensor device 800to a computing device such as computing device 750 shown in FIG. 21.Such a configuration would enable sensor device 800 to transmit data toand receive data from the computing device 750, for example a computingdevice worn on the wrist. The computing device could be used to enable auser to input data, which may then be stored therein or transmitted tosensor device 800, and to display data, including data transmitted fromsensor device 800. The configuration would also allow for computingtasks to be divided between sensor device 800 and computing device 750,referred to herein as shared computing, as described in detail inconnection with FIG. 21.

As shown in FIG. 27, PCB 860 may include proximity sensor 1000 which iscoupled to processing unit 900 for sensing whether sensor device 800 isbeing worn on the body. Proximity sensor 1000 may also be used as a wayto automatically power on and off sensor device 800. Proximity sensorpreferably comprises a capacitor, the electrical capacitance of whichchanges as sensor device 800 gets closer to the body. PCB 860 may alsoinclude sound transducer 1005, such as a ringer, coupled to processingunit 900 through driver 1010.

Sensor device 800 may also be provided with sensors in addition to thoseshown in FIG. 27, such as those taught by U.S. Pat. No. 5,853,005, thedisclosure of which is incorporated herein by reference. The '005 patentteaches a sound transducer coupled to a pad containing an acoustictransmission material. The pad and sound transducer may be used to senseacoustic signals generated by the body which in turn may be convertedinto signals representative of physiological parameters such as heartrate or respiration rate. In addition, rather than being integrated insensor device 800 as part of one or more of housing 805, flexiblesection 810 or strap 811, a sensing apparatus as taught by the '005patent may be provided separate from sensor device 800 and be coupled,wired or wirelessly, to sensor device 800. According to the '005, thesound or acoustic transducer is preferably a piezoelectric, electret, orcondenser-based hydrophone, similar to those used by the Navy in sonarapplications, but can be any other type of waterproof pressure andmotion sensing type of sensor.

The sensing apparatus as taught by the '005 patent is an example of whatshall be referred to herein as a non-ECG heart parameter sensor, meaningthat it has the following two qualities: (1) it does not need to makemeasurements across the torso using at least two contact separated bysome distance; and (2) it does not measure electrical activity of theheart. The sensing apparatus as taught by the '005 patent has been shownto be capable of detecting heart rate information and informationrelating to individual beats of the heart with high reliability undercertain circumstances, depending primarily on factors including theproximity of the apparatus to the heart, the level of ambient noise, andmotion related sound artifacts caused by the movement of the body. As aresult, the sensing apparatus as taught by the '005 patent is mostreliable when worn in an ambient environment with a low level of ambientnoise and when the body is not moving.

Certain characteristics, sensors and sensing capabilities of sensordevice 800 are able to improve the reliability and accuracy of anacoustic-based non-ECG heart parameter sensor 1012 such as the sensingapparatus as taught by the '005 patent that is incorporated therein orcoupled thereto. For example, in one specific embodiment, sensor device800 is particularly suited to be worn on the upper arm. The upper arm isa good location for a sensor device 800 having an acoustic-based non-ECGheart parameter sensor 1012 incorporated therein because it is near theheart and provides a space for sensor device that allows it to beunobtrusive and comfortable to wear. In addition, ambient sound sensorshown at 975 in FIG. 27 may be used to filter out ambient noise from thesignals detected by the acoustic-based non-ECG heart parameter sensor1012 in order to isolate the sound signal originating from the body.Filtering of the signal produced by an acoustic-based non-ECG heartparameter sensor 1012 such as the sensing apparatus as taught by the'005 patent in this manner may be used both in the case where such anapparatus is incorporated in sensor device 800 and in the case where itis separated from but coupled to sensor device 800 as described above.

Furthermore, the sound generated from the motion of the body that is notcreated by the heart can be accounted for and adjusted for through theuse of a sensor or sensors that detect or that may be used to identifybody sounds generated as a result of motion of the body, such asaccelerometer 905 shown in FIGS. 27 and 29 or the body position ormuscle pressure sensors identified in Table 1. For example, footfallscreate sound within the body that can lower the signal to noise ratio ofan acoustic-based non-ECG heart parameter sensor 1012, which will likelyresult in false positive and false negative heart beat identifications.As is well known in the art, accelerometer 905 may function as afootfall indicator. Accelerometer 905 may thus be used to filter orsubtract out from the signal detected by the acoustic-based non-ECGheart parameter sensor 1012 signals related sound motion artifactscaused by the movement of the body such as by footfalls.

Several methodologies for performing the filtering or subtracting ofsignals described herein are known to those of ordinary skill in theart. Such filtering or subtracting of signals used in connection withthe monitoring of disparate signal, some used for noise cancellation andsome used for their direct measure, is also known as data integration.

Sensor device 800 may also be used to put parameters around and providea context for the readings made by a non-ECG heart parameter sensor 1012so that inaccurate reading can be identified and compensated for. Forexample, sensor device 800 may be used to detect real time energyexpenditure of the wearer as well as the type of activity in which thewearer is engaging, such as running or riding a bike. Thus, as anotherexample of how the sensors and sensing capabilities of sensor device 800may be used to increase the reliability and accuracy of a non-ECG heartparameter sensor 1012 through data integration, the energy expenditureand activity type information can be used to provide a context in whichthe heart related parameters detected by the non-ECG heart parametersensor 1012 can be assessed and possibly filtered. For example, ifsensor device 800 detects that a person is burning 13 calories perminute and is biking, and the non-ECG heart parameter sensor 1012 isindicating that the wearer's heart rate is 60 beats per minute, then itis highly likely that further filtration of the signal from the non-ECGheart parameter sensor 1012 is necessary.

Other well known non-ECG heart parameter sensing devices include, forexample, those based on micro-power impulse radar technology, thosebased on the use of piezo-electric based strain gauges, and those basedon plethysmography, which involves the measurement of changes in thesize of a body part as modified by the circulation of blood in thatpart. It will be appreciated that the performance of these devices mayalso be enhanced through the use of data integration as describedherein.

ECG heart parameter sensing devices may be used with the presentinvention. Co-pending U.S. application Ser. No. 10/940,889 entitledMethod and Apparatus for Measuring Heart Related Parameters filed Sep.13, 2004, which is assigned to the assignee of the present invention andthe reference of which is incorporated in its entirety herein byreference, discloses one such type of ECG device that may be used withthe invention, for example, by being incorporated into the sensingdevice or simply used to provide input to the overall inventive system,device, or method.

Another sensor that may be incorporated into the sensor device 800measures the pressure with which sensor device 800 is held against thebody of the wearer. Such a sensor could be capacitive or resistive innature. One such instantiation places a piezo-resistive strain gauge onthe back of the enclosure to measure the small deflection of the plasticas increasing force is applied. Data gathered from such a sensor can beused to compensate the readings of other sensors in sensor device 800according to the readings of such a sensor.

Also provided on PCB 860 and coupled to processing unit 900 is switch1015. Switch 1015 is also coupled to button 1020 provided on housing805. Button 1020, by activating switch 1015, may be used to enterinformation into sensor device 800, such as a time stamp to mark theoccurrence of an event such taking medication. Preferably, button 1020has a tactile, positive d-tent feedback when depressed, and a concaveshape to prevent accidental depression. Also, in the embodiment shown inFIGS. 22-26, flexible section 810 includes membrane 1022 that covers andseals button 1020. In the embodiments shown in FIGS. 30-32, a similarmembrane 1022 may be provided on flexible section 810, and, preferably,also on housing 805 such that button 1020 is sealed when housing 805 isremoved from flexible section 810. Alternatively, a hole may be providedin flexible section 810 exposing button 1020 and membrane 1022 whenhousing 805 is attached to flexible section 810. In addition, coupled toprocessing unit 900 on PCB 860 are LCDs and/or LEDs 1025 for outputtinginformation to the wearer. FIG. 28 shows an alternate embodiment ofsensor device 800 in which LCD 1025 is provided on a top face of housing805. As an alternative to LCDs or LEDs 1025, sensor device 800 mayinclude a prior art electrochemical display that retains its ability todisplay information even when power is no longer being provided thereto.Such a display is described in U.S. Pat. No. 6,368,287 B1, thedisclosure of which is incorporated herein by reference, and includes aplurality of markers comprising a miniature heating element and acoating of heat sensitive material. When current is passed through oneof the heating elements, it heats up, thereby inducing a change in thecolor of the coating material. The color change is permanent, even afterthe heating element cools down. Such displays are relatively inexpensiveand thus are well adapted for use in embodiments of sensor device 800that are designed to be disposable, possibly single use, items.

Oscillator 1030 is provided on PCB 860 and supplies the system clock toprocessing unit 900. Reset circuit 1035 is coupled to processing unit900 and enables processing unit to be reset to a standard initialsetting.

Finally, non-volatile data storage device 1040, such as a FLASH memorychip, is provided for storing information collected and/or generated bysensor device 800. Preferably, data storage device 1040 includes atleast 128 K of memory. Non-volatile program storage device 1045, such asa FLASH ROM chip, is provided for storing the programs required tooperate sensor device 800.

As an alternative, a microprocessor with integral A/D converters, datastorage, and program storage may be substituted for processing unit 900,A/D converter 915, data storage device 1040 and non-volatile memory1045. A suitable example of such a microprocessor is the TexasInstruments Model MSP430 processor.

Any component forming a part of sensor device 800 that comes in contactwith the wearer's skin should not, in a preferred embodiment, degrade indurometer, elasticity, color or other physical or chemical propertieswhen exposed to skin oils, perspiration, deodorant, suntan oils orlotions, skin moisturizers, perfume or isopropyl alcohol. In addition,such components preferably are hypoallergenic.

FIG. 29 shows an alternate embodiment of PCB 860 in which rechargeablebattery 950, voltage regulator 955, recharger 960 and USB cable 965 havebeen replaced by disposable AAA battery 1050 and boost converter 1055.Boost converter 1055 uses an inductor to boost the voltage of AAAbattery 1050 to the 3.0-3.3 V required to run the electronics on PCB860. A suitable boost converter 1055 is the model MAX1724 sold by MaximIntegrated Products, Inc. of Sunnydale, Calif.

Referring to FIGS. 30 and 31, an alternate embodiment of sensor device800 is shown in which housing 805 is removably attached to flexiblesection 810. As shown in FIGS. 30 and 31, housing 805 is provided withgroove 1060 along with outer edge thereof which is adapted to receivetherein tongue 1065 provided on the bottom side of flexible section 810for securely but removably attaching housing 805 to flexible section810. Through the interaction of groove 1060 and tongue 1065, housing 805may thus be readily popped in and out of flexible section 810. Such aconfiguration enables housing 805 to be readily attached to multipleflexible sections having sizes and shapes that are different thanflexible section 810 as long as the flexible section includes a tonguesimilar to tongue 1065. Such alternate flexible sections may be sizedand shaped to fit on particular parts of the body, such as the calf orthigh, and may comprise a garment such as a shirt having the tongue ortongues located in places of interest, such as the upper arm or upperleft chest, the latter enabling housing 805 to be positioned over theheart of the wearer. Co-pending U.S. application Ser. No. 09/419,600,owned by the assignee of the present application and incorporated hereinby reference, identifies several locations on the body that areparticularly well adapted to receive particularly sized and shapedsensor devices so as to avoid interference with the motion andflexibility of the body. As will be appreciated by those of skill in theart, groove 1060 and tongue 1065 may be swapped such that groove 1060 isprovided in flexible section 810 and tongue 1065 is provided on housing805. As will also be appreciated by those of skill in the art, multiplealternative structures exist for securely but removably attachinghousing 805 to flexible section 810. These alternative structuresinclude, without limitation, temporary adhesives, screws, a tight fitbetween having 805 and flexible section 810 that holds the two togetherby friction, magnets provided in each of housing 805 and flexiblesection 810, well-known snaps and snapping mechanisms, a threadedportion provided on housing 805 adapted to be received by threads inflexible section 810, an O-ring or similar elastic band adapted to fitaround a portion of flexible section 810 and into a groove provided inhousing 805 when flexible section 810 is placed over housing 805, ormerely pressure when housing 805 is placed on the body and flexiblesection 810 is placed thereover and attached to the body such as bystrap 811. Referring to FIG. 32, a still further alternative structurefor removably securing flexible section 810 to housing 805 is shown inwhich flexible section 810 comprises and elastic or similar band that isadapted to fit into a groove 1062 provided in housing 805. Housing 805and flexible section 810 may then be placed on the body and held inplace by strap 811 or the like inserted through gaps 1064 betweenhousing 805 and flexible section 810.

FIG. 33 shows an alternate embodiment of sensor device 800 as shown inFIGS. 30 and 31 that is adapted to automatically adjust or alter theoperating parameters of sensor device 800, such as its functionality,settings or capabilities, depending on the particular flexible sectionto which housing 805 is attached. For example, the calculation of aparameter, such as energy expenditure, may depend on information that isparticular each individual, such as age, height, weight, and sex. Ratherthan having each individual enter that information in sensor device 800each time he or she wants to wear the device, each individual that isgoing to wear the device could enter the information once and have theirown flexible section that causes sensor device to make measurementsbased on his or her particular information. Alternatively, the memory insensor device 800 for storage of user data may be divided into severalcompartments, one for each user, so as to avoid co-mingling of userdata. Sensor device 800 may be adapted to alter where collected data isstored depending on the particular flexible section that is being used.In addition, sensor device 800 may be calibrated and recalibrateddifferently over time depending on the particular flexible section towhich housing 805 is attached as it learns about each particular wearerand his or her habits, demographics and/or activities.

According to a particular embodiment, housing 805 is provided with firstmagnetic switch 1070 and second magnetic switch 1075, each on PCB 860.Provided on or inside flexible section 810, such as by an insert moldingtechnique, is magnet 1080. Magnet 1080 is positioned on or insideflexible section 810 such that it aligns with and thereby activates oneof first magnetic switch 1080 and second magnetic switch 1075 whenhousing 805 is attached to flexible section 810. In the embodiment shownin FIG. 33, second magnetic switch 1075 will be activated. A secondflexible section 810 similar to flexible section 810 shown in FIG. 33will also be provided, the difference being that the magnet 1080provided therewith will be positioned such that first magnetic switch1070 is activated when housing 805, the same housing 805 shown in FIG.33, is attached to the second flexible section 810. Housing 805, and inparticular processing unit 900, may be programmed to alter itsfunctionality, settings or capabilities depending on which one of firstmagnetic switch 1070 and second magnetic switch 1075 is activated, i.e.,which particular flexible section 810 is being used. Thus, a husband andwife may share a single housing 805 but have different flexible wings810 with magnets 1080 located in different places. In such a case,housing 805 may be programmed to operate with functionality, settings orcapabilities particular to the husband when first magnetic switch 1070is activated, and with functionality, settings or capabilitiesparticular to the wife when second magnetic switch 1075 is activated.Although only two magnetic switches are shown in FIG. 33, it will beappreciated that multiple magnetic switches and multiple flexiblesections may be used to allow sensor device 800 to be programmed formultiple wearers, such as an entire family, with each family memberhaving his or her own flexible section. As still a further alternative,multiple flexible sections may be provided that are adapted to be wornon different parts of the body, each having a magnet placed in adifferent location. Housing 805 may then be programmed to havefunctionality, settings or capabilities particular to the type ofsensing to be done on each different part of the body, with magneticswitches placed so as to be activated when housing 805 is attached tothe appropriate flexible section. Sensor device 800 according to thisembodiment is thus a “smart” device. As will be appreciated by one ofskill in the art, many alternatives to first and second magneticswitches 1070 and 1075 and magnet 1080 may be used to provide thefunctionality described in connection with FIG. 33. Such alternativesinclude, without limitation, mechanical switches provided in housing 805that are activated by a protruding portion, such as a pin, provided at aparticular location on flexible section 810, optical switches comprisingan array of light sensors provided in housing 805 that are activatedwhen the surrounding light is blocked, reflected or filtered in aparticular way with one or more translucent sections and a singleopaque, reflective or filtering section being selectively provided onflexible section 810 at particular locations, the translucent sectionsnot activating the corresponding optical switches and the opaque,reflective or filtering section activating the corresponding opticalswitch, electronic switches provided in housing 805 activated by aconductor provided in particular locations in flexible section 810. Asstill a further alternative, housing 805 may be provided with multipleswitches and each flexible section 810 may be provided with one or moreswitch activators positioned to activate certain selected switches. Theoperating parameters of housing 805 would in this embodiment be adaptedto change depending upon the particular set of one or more switches thatare activated. This embodiment thus employs an encoding scheme to alterthe operating parameters of housing 805 depending on which flexiblesection 810 is used. As still a further alternative, housing 805 may beprovided with a single switch adapted to alter the operating parametersof housing 805 depending upon the way in which or state in which it isactivated, such as by the properties of the switch activators. Forexample, the switch may be a magnetic switch that is activated aplurality of different ways depending upon the magnetic level orstrength of the magnet provided in each flexible section 810. Aplurality of flexible sections 810 could then be provided, each having amagnet of a different strength. In addition, any particular flexiblesection 810 may be provided with a plurality of magnets having differentstrengths with each magnet being able to activate the switch in housing805 in a different manner. Such a flexible section 810 would be able toselectively trigger different operating parameters of housing 805, suchas by rotating a portion of flexible wing 805 to align a particularmagnet with the switch. As an alternative, the switch could be anelectrical switch and the switch activators could be conductors havingdifferent resistances. The switch would, in this embodiment, beactivated in different ways depending on the measured resistance of theswitch activator that closes the circuit.

Referring to FIG. 34, as still a further embodiment of sensor device800, housing 805 may be provided with adhesive material 1085 on a backside thereof to enable housing 805 to be removably attached to selectedportions of the body, such as the upper left chest over the heart,without flexible section 810. Adhesive material 1085 may be anywell-known adhesive that would securely attach housing 805 to the bodyand enable it to be worn for a period of time, but that would alsoreadily enable housing 805 to be removed from the body after use.Adhesive material 1085 may comprise, for example, a double sidedadhesive foam backing that would allow for comfortable attachment ofhousing 805 to the body. Furthermore, housing 805 may be made of awell-known flexible plastic film or the like, such as that taught inU.S. Pat. No. 6,368,287 B1, the disclosure of which is incorporatedherein by reference, that would, due to low cost, enable sensor device800 to be disposable. Such a disposable sensor device may also includean electrochemical display described above to enhance its disposability.In an embodiment adapted for placement over the upper left chest or anyother appropriate region for detecting heart related parameters, sensordevice 800 would include one or more sensors described herein forsensing heart related parameters such as heart rate, beat-to-beat orinterbeat variability, ECG or EKG, pulse oximetry, heart sounds, such asdetected with a microphone, and mechanical action of the heart, such asdetected with ultrasound or micro-pulse radar devices.

FIGS. 35A-H and 36A-H illustrate aspects of the present inventionrelating to the ergonomic design of sensor device 800. Referring toFIGS. 35A and 35B, a housing 1100 of a prior art sensor device having arectangular cross-section is shown resting on the body 1110 of a wearerof the prior art sensor device. As seen in FIG. 35B, when body 1110flexes and forms a concavity, as may happen many times each minute onvarious parts of the body or for extended periods of time depending onthe position of various body parties during particular activities, asignificant portion of housing 1100 is caused to be removed from body1110. When housing 1100 is caused to be removed in this manner, theability of the prior art sensor device to accurately make measurementsand collect data will be jeopardized, especially for any readings to betaken near the center of the cross-section indicated by the arrows inFIG. 35B.

FIGS. 35C-H illustrate a cross-section of housing 805 of sensor device800 taken along lines C-C shown in FIG. 23 according to various aspectsof the present invention. The cross-section shown in FIGS. 35C-H istaken near the middle portion of housing 805 shown in FIG. 23 betweenGSR sensors 825. As seen in FIG. 35C, bottom surface 1115 of housing 805is provided with a generally convex shape such that, when body 1110flexes and forms a concavity, a substantial portion of bottom surface1115 of housing 805 remains in contact with body 1110 by fitting intothe concavity. As seen in FIG. 35D, when body 1110 flexes in theopposite direction so as to create a convexity, the center portion ofhousing 805, indicated by the arrow in FIG. 35D, remains in contact withbody 1110. As shown in FIG. 35E, this is true even if housing 805 wereto rock within the concavity formed in body 1110. Referring to FIG. 35F,body 1110 may, at times, flex to an extreme degree, i.e., more than theanticipated maximum that it was designed for, such that, even if bottomsurface 1115 is provided with a convex shape, it may still cause bottomsurface 1115 to be removed from body 1110. A solution to this problem isillustrated in FIG. 35G, wherein the lateral ends 1120A and 1120B ofhousing 805 are provided with radiused portions 1125A and 1125B,respectively adjacent to and including opposite lateral ends of bottomsurface 1115. Radiused portions 1125A and 1125B enable housing 805 tosit lower and fit into the concavity created when body 1110 flexes to anextreme degree. In addition, radiused portions 1125A and 1125B providefor more comfortable wear as they eliminate sharp edges 1130A and 1130Bshown in FIG. 35F that contact body 1110. FIG. 35H shows how body 1110will tend to conform to the shape of housing 805 due at least in part tothe viscosity of the skin when body 1110 is in a relaxed condition.

FIG. 36A shows a cross-section of housing 1100 of prior art sensordevice taken along a line perpendicular to the line on which thecross-section shown in FIGS. 35A and 35B was taken. As seen in FIG. 36A,when housing 1100 is placed on a convex portion of body 1110,significant portions of housing 1100, specifically the lateral endsthereof indicated by the arrows in FIG. 36A, are not in contact body1110. FIGS. 36B-H show a cross-section of housing 805 according tovarious aspects of the present invention taken along lines D-D shown inFIG. 23. As seen in FIG. 36B, bottom surface 1115 of housing 805 isprovided with a generally concave shape adapted to receive the convexportion of body 1110. Referring to FIG. 36C, lateral ends 1130A and1130B may be provided with radiused portions 1135A and 1135B adjacent toand including opposite lateral ends of bottom surface 1115, which allowhousing 805 to rest in closer contact with body 1110, even when body1110 flexes to an extreme degree, i.e., more than the anticipatedmaximum that it was designed for, and remove sharp edges 1140A and 1140Bshown in FIG. 36B, providing for more comfortable wear. As shown in FIG.36D, body 1110 will tend to conform to the shape of housing 805 whenbody 1110 is in a relaxed condition. As shown in FIGS. 36E and 36F, goodcontact with body 1110 is maintained at the points illustrated by thearrows when body 1110 is flexed in a manner that decreases the convexshape thereof or that creates a convexity therein. Thus, it will beappreciated that it is advantageous to place sensors or sensing elementsat the points indicated by the arrows because those points will tend toremain in contact with body 1110. FIGS. 36G and 36H, showing, forexample, heat flux skin interface component 835 and skin temperatureskin interface component 840 placed at the points indicated by thearrows, illustrate this point. As seen in FIGS. 36G and 36H, there ismore than point contact between body 1110 and skin temperature skininterface component 840.

FIG. 37 is an isometric view of housing 805 according to an embodimentof the present invention in which bottom surface 1115 has both thegenerally convex shape shown in FIGS. 35C-H and the generally concaveshape shown in FIGS. 36B-H. Specifically, bottom surface 1115, which isthe inner surface of housing 805 for mounting adjacent to the body ofthe wearer, includes a longitudinal axis 1141 and a transverse axis1142. Bottom surface 115 has a generally concave shape having an axis ofconcavity 1143 that is coincident with longitudinal axis 1141, meaningthat it runs in a first direction from first lateral end 1144 of innersurface 1115 to second lateral end 1145 of inner surface 1115. Bottomsurface 1115 has a generally convex shape having an axis of convexity1146 that is coincident with transverse axis 1142, meaning that it runsin a second direction from third lateral end 1147 of inner surface 1115to fourth lateral end 1148 of inner surface 1115. As seen if FIG. 37,the first and second directions, and longitudinal axis 1141 andtransverse axis 1142, are generally perpendicular to one another.

Referring to FIGS. 38A-D, it will be appreciated that housing 805 havinga flat top surface 1150 and flat lateral ends 1130A and 1130B may tendto be jostled and bumped by object 1155, such as a wall or door or thecorner or edge of a drawer, cabinet or desk, thereby moving housing 805on body 1110 because such flat surfaces are not well adapted to deflectobject 1155. Movement of housing 805 on body 1110 will detrimentallyeffect the ability of sensor device 800 to accurately make measurementsand collect data. FIGS. 39A-G illustrate various aspects of the presentinvention that are adapted to deflect object 1155 and substantiallyprevent movement of housing 805 on body 1110. In addition, the formsshown in FIGS. 39A-G increase the durability of sensor device 800 andmake it easier to put on and wear clothing and the like, such as awetsuit, over sensor device 800. As seen in FIG. 39A, housing 805 mayhave tapered sides 1160A and 1160B such that the width of housing 805decreases in the direction from bottom surface 1115 to top surface 1150.Alternatively, referring to FIG. 39B, top surface 1150 of housing 805may have a convex shape. As a further alternative, as seen in FIG. 39C,housing 805 may be provided with radiused portions 1165A and 1165B thatmeet with radiused portions 1135A and 1135B such that the lateral endsof housing 805 have a substantially semicircular shape. As shown in FIG.39D, housing 805 may have both tapered sides 1160A and 1160B and a topsurface 1150 with a convex shape. FIG. 39E is a modification of housing805 shown in FIG. 39E in which the points 1170A and 1170B where radiusedportions 1135A and 1135B meet tapered sides 1160A and 1160B,respectively, are themselves radiused. FIG. 39F is a variation ofhousing 805 shown in FIG. 39E having elongated tapered sides 1160A and1160B. FIG. 39G shows how the ability of housing 805, such as theembodiment shown in FIG. 39E, to deflect object 1155 may be enhanced bythe addition of flexible section 810 having a substantially convex outersurface. In addition, an air channel is provided between flexiblesection 810 and body 1110 to allow for heat to flow away from body 1110.

Referring to FIG. 40, a top plan view of a data input and output,abbreviated I/O, device 1200 is shown. FIG. 41 is a partialcross-sectional view of I/O device 1200 taken along lines A-A in FIG.40. According to one embodiment of the present invention, I/O device1200 is in electronic communication with sensor device 1201 shown inFIG. 40 through communications connection 1230, which may comprise awired connection or a wireless connection as described elsewhere herein.Sensor device 1201 detects human physiological and/or contextualparameters, and may be any one of sensor device 400 shown in FIGS.12-17, stand alone sensor device 700 shown in FIG. 21, or sensor device800 shown in FIGS. 22-26. I/O device 1200 includes housing 1205 and LCD1210 attached to housing 1205. Various alternative display devices maybe used instead of an LCD for displaying information, and suchdisplaying of information and display devices are not limited to visualdisplay devices, but may include various tactile or audible displays asdescribed elsewhere herein. LCD 1210 may display information relating tothe human physiological and/or contextual parameters detected by sensordevice 1201 that is transmitted to I/O device by sensor device 1201 overcommunications connection 1230. Thus, I/O device 1200 may display thesame information and give the same feedback that any of the previouslydescribed sensor devices. I/O device 1200 also includes button 1215 anddial 1220. Dial 1220 is moveably mounted within groove 1225 provided inhousing 1205 such that dial 1220 is free to rotate about the top surfaceof housing 1205 in both clockwise and counter-clockwise directionswithin groove 1225. Button 1215 and dial 1220 may be used to enter orinput information into I/O device 1200 for subsequent storage in and useby I/O device 1200 and/or transmission to sensor device 1201. Thus, LCD1210 may also display information that is entered or input into I/Odevice 1200, or information generated from such entered or inputinformation. I/O device 1200 may take on any number of forms, including,but not limited to, a watch-like form adapted to be worn on the wrist, aform that may be clipped to or integrated within a bag or clothing, orotherwise easily carried in a pocket or a bag, a form similar to wellknown commercially available pagers or PDAs, a form that may beremovably, such as magnetically, attached to sensor device 1201 oranother apparatus such as a car dashboard, or the form of a key fob. I/Odevice 1200 could also be a separate electronic device such as a weightscale, in which case the weight scale may comprise a sensor thatcommunicates information to sensor device 1201.

It will be appreciated that, in the embodiment where sensor device 1201is stand alone sensor device 700, I/O device 1200 may perform the manualdata entry functions indicated by and described in connection withreference numeral 715 in FIG. 21. Furthermore, in this embodiment, I/Odevice 1200 may be the computing device 750 shown in FIG. 21. Asdescribed in connection with FIG. 21, this configuration providesseveral possibilities for data collection, generation and display.Specifically, sensor device 1201, as described in connection with standalone sensor device 700 shown in FIG. 21 and the subject of co-pendingapplication Ser. No. 09/923,181 owned by the assignee hereof, maycollect and/or generate data indicative of various physiological and/orcontextual parameters of the user, data manually input by the user, suchas by using button 1215 and dial 1220, and/or data input as a result ofdevice-to-device interaction shown at 720 and 725 in FIG. 21. Sensordevice 1201 may then generate derived data and analytical status datawhich may be transmitted to I/O device 1200 for display. Alternatively,sensor device 1201 may be programmed to generate derived data, which,along with the data collected by sensor device 1201, may be transmittedto I/O device 1200, and 110 device 1200 may be programmed and/orotherwise adapted to include the utilities and algorithms necessary tocreate analytical status data based on the data indicative of one ormore physiological and/or contextual parameters, the data derivedtherefrom, the data manually input by the user and/or the data input asa result of device-to-device interaction. The derived data and theanalytical status data so created may be displayed to the user with LCD1210. As still a further alternative, the data indicative of variousphysiological and/or contextual parameters, the manually input data,and/or the data input as a result of device-to-device interaction may betransmitted to I/O device 1200, and I/O device 1200 may be programmedand/or otherwise adapted to include the utilities and algorithmsnecessary to create derived data and/or analytical status data from theforegoing sources of data, all of which may then be displayed to theuser with LCD 1210. I/O device 1200 may also use the information inputinto it, such as by using button 1215 and dial 1220, to create deriveddata and/or analytical status data, or may use data sensed by a sensorprovided on I/O device 1200 as described elsewhere herein for the samepurpose. In addition, the generation of such data may be shared with oroffloaded to a separate computing device in electronic communicationwith I/O device 1200, such as a local PC or a remote server. In each ofthe foregoing embodiments, I/O device may be in electronic communicationwith and transmit data to still another device, such as a computingdevice or an earpiece or tactile communications device worn by afirefighter or other first responder or a runner. In this case, I/Odevice 1200 acts as a relay of information. In the case of thefirefighter or other first responder, the data may indicate an importantphysiological state, such as level of hydration, as determined by sensordevice 1201, and in the case of a runner, the data may indicate caloricexpenditure or distance traveled.

As known in the art, a number of configurations exist for constructingI/O device 1200 so that button 1215 and dial 1220 may be used to inputinformation into I/O device 1200. Such buttons and dials arecommercially available from Duraswitch Industries, Inc. located in Mesa,Ariz. under the names PUSHGATE™ pushbutton and thiNcoder™ ROTOR,respectively. U.S. Pat. No. 5,666,096, the disclosure of which isincorporated herein by reference, is owned by Duraswitch Industries,Inc. and describes the rotary switch technology used in the thiNcoder™ROTOR switch. The '096 patent describes a rotary switch including abottom substrate layer and a top membrane layer separated by anon-conductive spacer. The internal surface of the membrane layercarries a set of electrodes which define the spaced contacts of at leastone electrical switch. The membrane layer also carries an electricallyconductive metallic armature, in the form of a flat circular disc, thatis received in an annular opening provided in the spacer. The switchfurther includes a rotatable actuating knob that carries a coupler inits underside. The coupler is a magnet which may be molded or otherwiseentrapped in the knob. The coupler forces the armature against theinternal surface of the membrane by means of the magnetic fieldoriginating from the coupler. The coupler functions both to create theswitch contact pressure as well as to drag the armature from one contactto another when a user rotates the knob. In operation, when the knob isrotated, the coupler rotates with the knob and, by virtue of themagnetic coupling between the coupler and the armature, the armaturerotates with the knob as well. As the armature rotates, it moves intoand out of shorting contact with the contact or contacts on themembrane. When the armature is in shorting contact with a contact, thecorresponding switch is closed. As will be appreciated by those of skillin the art, various encoding schemes are known for converting theactuation of one or more switches into information that may be used by aprocessor or other device coupled to the switch.

Alternatively, U.S. Pat. No. 6,225,980 B1, the disclosure of which isincorporated herein by reference, describes a rotary dial input devicefor portable computers including an insulating member overlying aprinted circuit board, a spine rigidly connected to the printed circuitboard, a rotatable dial, a switch ring carried by the dial and a snapring rigidly connected to the dial. The dial, the switch ring and thesnap ring rotate together around the periphery of the spine. The switchring carries at least two magnets located 180° apart, and a plurality ofHall effect sensors are mounted on the printed circuit board and liejust under the surface of the insulating material. The position of themagnets relative to any of the Hall effect sensors may be used togenerate an output signal based on the position of the dial. The '980patent also describes a spring-based mechanism for enabling the dial tobe moved between first and second vertical positions, wherein thesprings biases the dial toward the first vertical position and downwardpressure is required to move the dial toward the second verticalposition. An additional magnet is included on a flexible arm carried bythe switch ring. Upon movement of the dial from the first verticalposition to the second vertical position, the magnet is moved in adirection toward another Hall effect sensor mounted on the printedcircuit board. This Hall effect sensor produces a signal whenever thedial is depressed, which signal may be used to control the associatedportable computer. The '980 patent further states that a momentaryswitch may be provided, such as in the center of the dial, for producinganother computer control signal.

According to the '980 patent, the multiple switch rotary dial inputdevice described therein, that generates signals from the rotation ofthe dial and the depression of the dial and/or a momentary switch, maybe used in place of conventional mouse input devices as a mechanism forcontrolling and entering information into a computer. For example, the'980 patent states that the dial may be rotated to scroll through a listof items appearing on a display device of the computer, and the dial ormonetary switch may be depressed to select an identified item. In thepreferred embodiment, the dial cannot be depressed while it is beingrotated and vice versa.

As another example, U.S. Pat. No. 5,959,611, the disclosure of which isincorporated herein by reference, describes a portable computer systemincluding a CPU, an input interface, a display and an input device,wherein the input device comprises a rotary switch or dial and threeon/off switches. The rotary switch may be a 16 position, binary codedrotary switch which outputs a four-digit gray code representing theposition of the switch. As is known in the art, a gray code is a specialbinary encoding scheme in which adjacent numbers or positions have codesthat differ in only one bit position. The on/of switches may bemomentary push button switches positioned so as to surround the rotaryswitch.

The input interface translates the rotational movement of the rotaryswitch and the depressions of the on/off switches into dataappropriately formatted for the CPU. Specifically, four conductors carrya first input signal produced by the rotary switch indicative of itsposition, and each of three separate conductors carry second inputsignals generated by depression of each of the on/off switches. The '611patent states that the first input signal may be used to sequentiallyidentify, through rotation of the dial, information appearing on thedisplay, and the second input signals may be used to select anidentified piece of information. The input interface may be implementedusing a PIC microcontroller that is programmed to encode the first andsecond input signals into, for example, an eight bit byte transmitted tothe CPU consisting of one byte for each switch depression and every turnof the rotary switch. Such an eight bit byte, according to the '611patent, consists of six significant bits. Bits 5 and 6 represent therotary switch turning clockwise and counterclockwise, respectively. Ifone of those bits is set to one, thereby indicating either a clockwiseor counter-clockwise rotation, then bits 1 through 4 represent the graycode input signal. If both of those bits are set to zero, then bits 1through 4 represent the depression of one of four possible on/offswitches, only three of which are actually in use in the devicedescribed in the '611 patent. In other words, if any of bits 1 through 4is set to one, then the corresponding switch was just depressed.

As is known in the art, particular portions or zones of a computerdisplay showing a particular character, word or image can be selected,using a mouse or other input device, to cause the computer to perform anaction. The '611 patent refers to such zones as hot spots. According tothe '611 patent, a user can sequentially identify or step through hotspots provided on the display by rotating the rotary switch in aclockwise direction. Rotation of the rotary switch in acounter-clockwise direction enables the user to step through the hotspots in the reverse order. When the desired hot spot is identified,such as by being made bold or otherwise highlighted, any one of theon/off switches may be depressed to select the identified hot spot,thereby causing the computer to perform an action. Thus, the inputdevice described in the '611 patent may be used to input informationinto and control a computer much like a conventional mouse.

FIG. 42 is a reproduction of FIG. 5 of the '611 patent and is a blockdiagram illustrating the operation of the software that enables theinput device to identify and select hot spots. In FIG. 42, a screen isdrawn or redrawn at step 6200. Thereafter, process control proceeds tostep 6200 in which the software awaits input from the user, i.e., theeight bit byte of information provided to the CPU from the inputinterface. When input is received from the user, step 6600 determines ifa selection has been made, i.e., whether of the of on/off switches hasbeen depressed. If none of the switches has been depressed, then theinput must be rotation of the rotary switch and process control proceedswith step 6800. At step 6800, a determination is made as to whether therotary switch has been rotated in a clockwise direction. If so, processcontrol proceeds with step 7200 wherein the next hot spot becomes theactive hot spot. If the rotary switch has been rotated in acounter-clockwise direction, process control proceeds with step 7000 inwhich the previous hot spot becomes the current hot spot. After eitherstep 7000 or 7200, process control returns to step 6400 to awaitadditional user input.

If at step 6600 a selection was made, process control proceeds with step7400 to determine if a system command had been invoked. If not, the typeof hot spot is checked at step 7600, the relevant code is executed, andthe screen is redrawn at step 6200. If, on the other hand, a systemcommand is invoked at step 7400, at step 7800 an execution of the nextscreen or previous screen, as appropriate, is performed and theappropriate screen is redrawn at step 6200. Thereafter, process controlreturns to step 6400 to await additional user input. In this manner, therotation of the rotary switch coupled with operation of the push-buttonswitches controls the hot spots and ultimately controls the informationdisplayed on the display and the actions taken by the computer. Those ofordinary skill in the art will recognize that the process illustrated inFIG. 42 can be implemented in software in a variety of ways.

Thus, as is known in the art and as taught by, for example, the '980 and'611 patents, dial 1220 may be used to step through or toggle between oramong various input or command or control possibilities presented on LCD1210 by selectively rotating dial 1220 in either the clockwise orcounter-clockwise direction. As dial 1220 is rotated, the various inputor command or control possibilities are highlighted. Highlighted itemsmay be selected and a corresponding action commenced by pressing button1215, or alternatively dial 1220 itself, in which case dial 1220 acts asboth a dial and a button as those terms are used herein such that thedevice in question would be considered to have both a dial and a button.One alternate example of dial 1220 is the knob on the side of a watchthat rotates about the side external surface of the watch.

As an alternative to dial 1220, one or more buttons, such as an upbutton and a down button or left and right buttons, may be used to stepthrough or toggle between or among various input or command orpossibilities presented on LCD 1210. In this embodiment, button 1215 maystill be used to select and commence a highlighted items. As a furtheralternative, I/O device 1200 may be provided with voice recognitionsoftware and voice commands may be used to step through or togglebetween or among various input or command or possibilities presented onLCD 1210. Voice commands may also be used to select and commence ahighlighted items. As still a further alternate embodiment, voicecommands in combination with voice recognition software may be used todirectly enter information, such as nutrition information describedbelow, into I/O device 1200.

Referring to FIGS. 43A-F, an embodiment of the present inventionincluding I/O device 1200 is shown in which energy related data for anindividual is collected or generated by I/O device 1200 and sensordevice 1201 and displayed by I/O device 1200 on LCD 1210. As seen inFIGS. 43 A-C, the energy related data may include calories consumed andcalories burned by the individual over specific time periods such as aday, a week or a month. In FIG. 43A, this data is presented in a formatthat provides a comparison to a predetermined goal for each value. Theexample shown in FIG. 43A shows that a daily goal of 2000 caloriesconsumed was set by the individual and that the individual has consumed1,483 calories on the day in question, and that a daily goal of 2,400calories burned was set by the individual and that the individual hasburned 2,750 calories on the day in question. Referring to FIGS. 43 Band C, the data is presented in a format referred to as energy balancein which the amount of calories consumed by the individual is comparedto the amount of calories expended or burned by the individual fordaily, weekly or monthly periods. It will be appreciated that theindividual may toggle between the goal based and energy balance formatsjust described, and among the various time periods within each, byrotating dial 1220 and, in one embodiment, also pressing button 1215.Depending upon the rotation of dial 1220 and, in one embodiment, uponpressing of button 1215, appropriate information is displayedsequentially on LCD 1210. For example, in FIG. 43A, LCD 1210 is showndisplaying data in the goal based format for a daily time period. LCD1210 may be caused to display the data in the goal based format for aweekly or monthly period by progressively rotating dial 1220 in theclockwise direction. Similarly, LCD 1210 may be caused to switch fromdisplaying data in the goal based format shown in FIG. 43A to displayingdata in the energy balance format for the various time periods byprogressively rotating dial 1220 in the counter-clockwise direction.

The calories burned data that is displayed by I/O device 1200 may,according to one embodiment of the present invention, be generated bysensor device 1201 from the physiological and/or contextual parametersit detects and thereafter transmitted to I/O device 1200 for storage,use in appropriate calculations and/or display. The calories burned datamay also be generated using data that is input by the user in additionto the detected parameters. Furthermore, the caloric consumption datathat is displayed by I/O device 1200 may, according to one embodiment ofthe present invention, be generated, preferably by I/O device 1200 butalso by sensor device 1201, from data input into I/O device 1200 by theindividual relating to foods consumed (as described elsewhere herein,caloric consumption data may also be generated using various detectedparameters in addition to information that is input manually).Specifically, I/O device 1200 may be provided with access to a useraccessible database of foods and corresponding caloric value. Such adatabase may be provided as part of I/O device 1200 itself, as in thecase of the preferred embodiment of the present invention, or I/O device1200 may be able to access a database stored and maintained on acomputing device located separately from the I/O device such as throughshort or long distance wireless or wired communications. Referring toFIG. 43D, LCD 1210 is shown displaying an ENTER NUTRITION menu screenthat may be accessible from, for example, a main menu screen presentedon LCD 1210 using dial 1220 and button 1215. When the individual eats aparticular food, he or she may enter it into I/O device 1200 for storageand/or use thereby by rotating dial 1220 until the FOOD DATABASE line ofthe ENTER NUTRITION menu screen shown on LCD 1210 is highlighted andthereafter pressing button 1215 to select same. Once the food databasehas been selected, the individual is, in this embodiment, presented withthe search screen shown on LCD 1210 in FIG. 43E. The individual maysequentially spell out the name of the food consumed by rotating dial1220 to each letter and selecting the letter by pressing button 1215.When the individual has finished spelling the food in question, he orshe rotates dial 1220 until SEARCH is highlighted and then pressesbutton 1215. In response, as shown in FIG. 43 F, I/O device 1200presents a list on LCD 1210 of foods that match the entered searchinformation. The individual may then select the appropriate food byrotating dial 1220 and pressing button 1215. When this is done, thecorresponding caloric information may be displayed to the user on LCD1210 and will be stored by I/O device 1200 as part of the caloricconsumption data for that day. The database may include severalsub-entries for each food that correspond to particular serving sizes,such as a 3 oz. slice of pie or a 6 oz. piece of chicken, and theappropriate caloric value associated therewith. As will be appreciatedby one of skill in the art, these sub-entries may be presented to theuser and selected using dial 1220 and button 1215 in the mannerdescribed above. Referring again to FIG. 43D, I/O device may also beused to store a list of favorite foods that are consumed frequently. Byselecting the FAVORITE FOODS line from the Enter Nutrition menu screenprovided on LCD 1210 and subsequently selecting the appropriate favoritefood, both done by using dial 1220 and button 1215, an individualeliminates the need to search through the database as described above.In addition, an individual may add a custom food and associated caloricvalue to the food database using dial 1220 and button 1215 by selectingthe ADD CUSTOM FOOD line from this Enter Nutrition menu screen providedon LCD 1210 and using a subsequently provided alpha-numeric entry screensimilar to that shown in FIG. 43E to enter the food name and caloricinformation. Once entered, this custom food will be accessible from thefood database. As will be appreciated to those of skill in the art, theinformation displayed on LCD 1210 may be shown in list menu or serialmenu format.

Although FIGS. 43D-F illustrate the use of a database of foodinformation according to one embodiment of the present invention, itwill be appreciated that any database of information may be used withI/O device 1200 without departing from the scope of the presentinvention. For example, the database could store a number of activities,such as walking, running or biking for a particular time period, and thecaloric expenditure associated with each. In such a configuration, I/Odevice 1200 would enable an individual to input and track his or hercaloric expenditure over a period of time. Furthermore, it will beappreciated that I/O device 1200 is not limited to receiving anddisplaying information relating to caloric consumption and expenditureas shown in FIGS. 43A-F. Instead, I/O device may receive and displaymany different types of information from one or both of sensor device1201 and the user, including, for example, information relating to sleepstates and patterns.

It is also possible to enter nutrition information in a considerablysimplified manner in any of several potential forms, including singledimensional point systems, single dimensional categorical ratingsystems, and multi-dimensional categorical rating systems. For a simpleexample of a single-dimensional point system, the user may select from a7 point scale, where each point value corresponds to a roughapproximation of the relative size of the meal in relation to the user'snormal sized meal. For an example of a categorical system, the user mayselect from the set {tiny, small, medium, large, and super-size} whendescribing a meal. An example of a multi-dimensional categorical systemis the grid system described below.

For each of these systems, the users are asked to score each meal(including snacks) according to the choice of scoring system. The user'sclassification of the meal, as identified by a classification identifierchosen by the user, is used as an input to an algorithm that estimatesthe caloric content of the meal. The algorithm that does thiscalculation may take other factors into consideration, including, butnot limited to, the time of day, the day of the week, the season,whether the day is a holiday, the user's past meal habits, the raw orderived values from a body monitoring product such as sensor device1201, demographic information, and trends in the user's reporting ofdata. The algorithm may be a simple look-up table where eachclassification identifier is associated with a caloric amount, but canbe more complicated as well.

Referring to FIG. 43G, an alternate interface 1250 displayed on LCD 1210for entering nutrition information into I/O device 1200 is shown whichsimplifies user interaction. In connection with interface 1250, usersare provided with a two-dimensional grid-based system based on grid 1255and are asked to rate each meal, including snacks, according to a gridsystem based on the size of the meal or snack, shown on the horizontalaxis of grid 1255, and the estimated caloric density of the meal orsnack (essentially the fat content), shown on the vertical axis of grid1255. The grid squares are then translated into caloric estimates (orcaloric estimate ranges) using any of a variety of algorithms. In oneembodiment, the grid squares correspond directly to caloric estimatesvia a lookup table derived from aggregate population statistics. Inanother, the corresponding caloric estimates are based on a weightedcombination of a user's own previous data and aggregate populationstatistics. The user may answer a pair of questions instead of directlychoosing a grid square. The pair of questions first may ask about thesize of the meal, and then may ask about the caloric density.

This system of quick caloric entry has been tested and verified in bothan in-house pilot study with ten subjects over several months conductedby the assignor of the present application and a brief three-day studyof 41 participants. In both studies, the following method was used. Foreach subject, the data from all of the other subjects was used togenerate caloric estimates for each grid category for each meal type.The estimates from that aggregate information were then compared to thecomputed caloric totals calculated from full diet diary entries. FIG.43I shows a scatter plot between the estimates of the caloric contentbased on the present invention and those computed from the full dietdiary entries for one of the subjects in the in-house study, and FIG.43J shows the relationship between the estimates of the caloric contentbased on the present invention and those computed from the full dietdiary entries for the three-day. The correlation between the estimatesof the in-house study and the diet diary caloric totals was 0.80, andthe estimates of the three-day study and the diet diary caloric totalswas 0.57, without any normalization by each subject's basal metabolicrate. This data, taken with the most simple of the embodiments of thesystem, strongly supports the premise that diet recording using a quickentry system can result in reasonably accurate estimates of a user'sdaily caloric intake.

Referring to FIG. 43H, a further alternate interface 1250 displayed onLCD 1210 for entering nutrition information into I/O device 1200 isshown which simplifies user interaction. In connection with interface1250, users are provided with a point system based on grid 1255 and areasked to score each meal, including snacks, according to a point systembased on the size of the meal (including snacks), shown on thehorizontal axis of grid 1255, and the estimated caloric density for themeal (including or snacks), shown on the vertical axis of grid 1255. Thepoints act as categories enabling the user to classify each meal,including any snacks, and thereby associate a caloric amount with themeal. Users may also be given a baseline size and calorie value to beassociated with each point level. For example, a 1 may be set to be ameal that is the size of a first having an estimated calorie value of300-500 calories, a 2 may be set to be a meal that is either the size ofa first having an estimated calorie value of 500-700 calories, or thesize of a first and a half with a calorie value of 300-500 calories, andso on, with a 7 being a super-size meal that exceeds any of the providedlevels. In addition, the meal score may further be weighted, bymultiplying the score by a weighting factor, depending on whether it isbreakfast, lunch, dinner or a snack. The user can use dial 1220, oralternatively one or more buttons or voice commands, to toggle among thescores or points shown in grid 1255 and button 1215 to select a score orpoint level. Each point level has associated therewith a caloric valueor amount, which may be a range of calories, that is saved for the mealin question. The associated caloric amounts may be a generic valuesdesigned to suit the public at large, or may be specific values tailoredto particular individuals. It will be appreciated that, depending on thegrid 1255, the user, in selecting a point level, may actually be makingtwo selections, one based on the horizontal axis of the grid (size ofmeal) and the other based on the vertical axis of the grid (caloricdensity of the meal). In addition, according to a particular embodiment,the I/O device 1200 is programmed to adjust its settings over time basedon information that is collected. For example, if a user begins a weekweighing 200 pounds and at the end of the week should weigh 197 poundsbased on the input nutrition and other information, but instead actuallyweighs 202 pounds, the problem could be that what the user thinks is a 1point meal is actually a 2 point meal. To account for this problem, I/Odevice 1200 can, over time learn and adjust or calibrate its settingsand how it does its calculations to personalize itself for the user by,for example, increasing the number of calories associated with a user'sclassification. This learning process thus increases the accuracy of I/Odevice 1200. One method for implementing this automatic calibration isto use Bayesian statistics and use an initial prior for the caloricvalue of the classifications based on aggregate user statistics and thento train it for the given user over time as data is entered into thesystem. As another embodiment, the system can allow the wearer to inputboth simplified dietary information (such as the grids shown in FIGS.43G and H) and full dietary information about the meals that are eaten.The caloric amounts from the full dietary information can easily becalculated and used to train the caloric estimates for each category. Inaddition, as I/O device learns, adjusts or calibrates, it may alsomodify the goals of the user and the program he or she is following. Asstill a further alternative, I/O device 1200 can take the information ithas accumulated over time and provide information automatically for auser. For example, if a user forgets to enter a lunch value, I/O devicemay be programmed to enter the average of a predetermined number of,such as the last ten or even all, lunch values for the missing lunch.This may be done automatically, or only after prompting the user forverification of the values and authorization to do so. Alternatively,I/O device may fill in such gaps by matching that days routine to aprevious day's routine, and using the lunch or other missing value fromthat day, thereby taking advantage of the fact that people tend to becreatures of habit.

Another aspect of the invention is that of automatic adaptation offeedback given to the user by sensor device 1201 or I/O device 1200. Thefeedback given to the user in this invention (e.g. “you might want torun an extra 10 minutes today”) can be given exactly when appropriate bytaking advantage of the system's ability to detect contexts and toauto-journal as describe elsewhere herein. For example, feedback foreating might be best given just before a meal, and exercise feedbackmight be best given right when the user is most likely to exercise.Furthermore, if the system has detected that the user has already joggedthat day, then an alternate suggestion can be given. Finally, the user'sresponse to feedback can be utilized to further adapt the choice of thegiven feedback. If the user never takes exercise suggestions, advice canfocus instead on nutrition. If the user tends to respond better tofeedback given in the morning, more feedback can be given in themorning. The method of noticing their response would be measured byadherence to the suggestions and by successful maintenance of a healthyeating balance, as well as by noticing the absence of “violent”responses such as hitting a button that turns feed back off, turning thedevice off, or abruptly taking off the device.

There are three main ways in which sensor device 1201 can calibrateitself to the user. First, the device can use an initial training orcalibration period where the user performs some additional tasks totrain the system. For example, the user can enter in a full diet diaryin addition to the quick estimates, allowing the system to learn theuser's own definitions for each meal classification. The user mightadditionally perform a program of activities (such as walking around theblock for at least 10 minutes or resting for 20 minutes) in order tocalibrate a subsystem for obtaining energy expenditure that may beprovided in sensor device 1201 and obtain personalized parameters forthe individual that are then used in later use of the system. Thesubsystem for obtaining energy expenditure may also be calibratedagainst gold standard data from, for example, a VO2 machine. The secondmethod involves repeating the training procedures (or a subset thereof)every so often. One example of this would be for a glucose levelprediction algorithm where, each week (for example), the user performs afinger-prick glucose test to calibrate the prediction system. The thirdmethod involved doing continual training while the user is using thesystem including sensor device 1201. For example, the system describedabove that utilizes discrepancies in predicted weights between thesystem's prediction and that reported by a scale to adjust the estimatedcaloric amounts for each category is an example of this type oftraining.

According to a further aspect of the present invention, the user can bequeried to answer questions that the sensor device 1201 or I/O device1200 can not figure out for itself, or about which it has too muchuncertainty. For example, the sensor device 1201 or I/O device 1200 mayhave enough information to ask the user only a single question aboutbreakfast, but may require more information for a morning snack that theuser doesn't have every day. The system can ask the questionsspecifically when the range of its uncertainty about a quantity is toolarge, and can thus minimize the input required from the user.

According to a further aspect of the present invention, I/O device 1200,sensor device 1201 and a computing device such as a PC or a PDA may beused together as a weight management system. Specifically, I/O device1200, such as a watch like device, is used to input and trackinformation relating to calories consumed by an individual and sensordevice 1201 is used to measure calories burned or expended by theindividual. The caloric expenditure information measured by sensordevice 1201 is transmitted, by wire or wirelessly, to I/O device 1200.I/O device 1200 then, based on the caloric consumption and caloricexpenditure information, displays to the individual a current rate ofweight loss or gain and/or an energy balance value on LCD 1210.According to a specific embodiment, sensor device 1201 assumes that theindividual is inactive if sensor device 1201 is not being worn, and usesthe individual's resting metabolic rate to calculate caloric expenditureduring such period.

In one embodiment, the individual, for each meal, including snacks,rather than inputting a specific food or foods selected from a databaseas described in connection with FIGS. 43D-43F, merely classifies eachmeal according to an indication of the estimated size of the meal (interms of an estimated caloric value) using classifiers such as small(S), medium (M), large (L) or extra large (XL). Each classifier isassigned a corresponding caloric amount, and I/O device 1200 stores forthe meal the caloric amount corresponding to the entered classifier. Toenable the individual to enter this information, I/O device 1200 firstdisplays on LCD 1210 a list of each meal possibility, i.e., breakfast,lunch, dinner or snack. The individual is able to toggle among theseselections using dial 1220 or one or more buttons, and select one usingbutton 1215. Once the meal classification is selected, I/O device 1200displays on LCD 1210 a list of the classifiers such as S, M, L, and XL.Again, the individual is able to toggle among these items using dial1220 or one or more buttons, and select one using button 1215. When oneof these classifiers is selected, the corresponding caloric amount issaved for the meal in question and is used to generate the caloricconsumption information used by I/O device 1200. I/O device 1200 may beprogrammed to prompt the individual to enter meal information if theindividual has not done so by a certain time or times each day.

In a preferred embodiment, the computing device is provided with weightmanagement software that enables the individual to input informationrelating to foods actually eaten during each meal using a database suchas that shown in FIGS. 43D through F. Based on the information that isinput, a specific caloric amount is assigned to each meal entry. Theindividual is also able to enter information relating to weight goals,such as how much weight the individual wants to lose and over what timeperiod the individual wants to lose the weight. Based on thisinformation, a target weight loss rate may be established for achievingthe input goal. In this embodiment, the individual, while enteringinformation into I/O device 1200 using the S, M, L, and XL classifiersystem, also enters information into the computing device using theweight management software for a predetermined time period. Sensordevice 1201 is in electronic communication, by wire or wirelessly, withthe computing device to enable information to be transmitted from thecomputing device to sensor device 1201. Specifically, the informationthat is transmitted from the computing device includes informationrelating to the weight goals, namely target weight loss amount, timeframe and rate, and information relating to the caloric amountassociated with each meal eaten by the individual based on the fooditems input into the computing device. Sensor device 1201 may thentransmit the information to I/O device 1200. Alternatively, I/O device1201 may be in electronic communication, by wire or wirelessly, with thecomputing device so that the information may be transmitted directly tothe I/O device 1200. According to an aspect of the present invention,I/O device 1200 compares the caloric amounts entered for each meal usingthe S, M, L, and XL classifiers with the caloric amounts entered foreach meal using the computing device and database of food informationover the predetermined time period, and make adjustments to the caloricamounts that are associated with each of the classifiers so that theymore accurately reflect calories actually consumed. Thus, in thisspecific embodiment, the individual enters nutrition information bothusing I/O device 1200 and the computing and database for a specifiedperiod of time, for example two weeks, after which the entry system onI/O device 1200 is calibrated or adjusted to bring the individual'sperception of what should be classified as S, M, L, or XL based oncalories in line with more accurate caloric data. After this initialperiod, the individual only enters nutrition information using I/Odevice 1200 and the S, M, L, and XL classifiers, and caloric data isrecorded for each meal depending on how the meal is classified.

In a preferred embodiment, I/O device 1200 is programmed to providesuggestions to the individual, in the form of information displayed onLCD 1210, on how to achieve the individual's weight goals. Thesesuggestions are based on the caloric expenditure and caloric consumptiondata that is logged by I/O device 1200. For example, if the individualis currently below the target weight loss rate of, for example, 1 poundper week, I/O device 1200 may display a message that instructs theindividual to walk for 55 minutes to bring the current weight loss rateup to 1 pound per week. The suggestions may be of many types, including,without limitation, actions for the individual to take, explanations forwhy the individual is experiencing certain things such as inability tolose weight, feedback regarding the individual progress toward goals,and/or relationships between or among the parameters being measuredand/or reported by sensor device 1201 and/or I/O device 1200. Thesuggestions may self adjust or learn based on the individual'sperformance toward goals. The substance of the suggestions may come froma number of sources, such as sensor device 1201 and/or I/O device 1200or a third party source, including a person such as a trainer or healthcare provider, a computing device such as a treadmill, or a remotecomputer, such as an Internet source.

As noted above, in one embodiment, I/O device 1200 displays a currentweight loss or gain rate on display 1200. The current weight loss orgain rate that is displayed on I/O device 1200 may be a daily, weekly ormonthly rate, or may be a rate calculated based on the total timeremaining until the weight loss target date. I/O device 1200 may beprogrammed to selectively display each of these rates depending on thedesires of the individual, such as by using dial 1220 or one or morebuttons to toggle among these various options.

FIG. 44 is a block diagram showing the components attached or otherwisecoupled to a printed circuit board (not shown) housed within housing1205 of an embodiment of I/O device 1200. Included among thesecomponents is processing unit 1300, which may be a microprocessor, amicrocontroller, or any other processing device that can be adapted toperform the functionality described herein. Connected to processing unit1300 are non-volatile data storage device 1305, such as a flash memory,chip for storing information input and/or transmitted to I/O device1200, and non-volatile program storage device 1310, such as a FLASH ROMchip, for storing the programs required for operation of I/O device1200. Also provided is reference database 1315 which may, as describedin connection with FIGS. 43D-F, be used to provide user accessible andselectable information for use by I/O device 1200 or sensor device 1201.As is known in the art, reference database 1315 includes a softwarecomponent for organizing and accessing data, and a memory component forphysically storing data. Also connected to processing unit 1300 are oneor both of wireless link 1320, such as an RF transceiver, connected toantenna 1325, and hardware interface 1330, such as a USB port, connectedto connector 1335. These components are used to implement communicationsconnection 1230 shown in FIG. 40, and may also be used to communicateelectronically with a wide variety of devices, such as a treadmill, aweight scale or a transceiving device adapted to act as a datacollection and storage hub. Driver 1350 and ringer/buzzer 1345 may alsobe connected to processing unit 1300 to provide audible and/or tactilefeedback to a user.

LCD 1210 and backlight 1350 for LCD 1210 are connected to processingunit 1300 through appropriate well known drivers 1355. Battery 1360,which may be disposable or rechargeable, provides power for I/O device1200 and is connected to processing unit 1300 through voltage regulator1365. Oscillator 1370 provides the system clock to processing unit 1300,and reset circuit 1375 enables processing unit 1300 to be reset to astandard initial setting. Finally, button 1215 and dial 1220 areelectronically connected to processing unit 1300 according to any knownmeans, such as those described in the '980 and '619 patents, which wouldenable button 1215 and dial 1220 to provide input or command or controlsignals to processing unit 1300.

According to an alternate embodiment of the present invention, I/Odevice 1200 may be adapted to operate on its own, without being incommunication with sensor device 1201. In this embodiment, a user mayenter information into I/O device 1200 as described herein and may useI/O device to store and track such information over time. For example,reference database 1315 may store food and activity related informationand a user may enter caloric consumption and caloric expenditure or burninformation as described in connection with FIGS. 43D-F. The enteredinformation would in this embodiment be stored in data storage device1305, and processing unit 1300 would be programmed to generate anddisplay the information shown in FIGS. 43A-C. In such an embodiment, RFlink 1320, antenna 1325, hardware interface 1330 and connector 1335would not be required since communication with sensor device 1201 is notnecessary, but may be included as optional enhancements. For furtheradded functionality, one or more sensors 1400, such as those describedin connection with sensor device 400, stand alone sensor device 700 andsensor device 800, may be, as shown in FIG. 45, attached to, supportedby or otherwise coupled to I/O device 1200, enabling it to collect dataindicative of physiological and/or contextual parameters. In onespecific embodiment, sensor 1400 may be a heart rate sensor in the formof a chest strap. In another specific embodiment, sensor 1400 may be anon-ECG heart parameter sensor such as that described in the '005patent. Sensor 1400 in this embodiment may be used in connection withheart rate information collected by sensor device 1201, such as ECGinformation obtained from the upper arm, to make pulse transit timemeasurements, which, as is known in the art, are an indication ofcardiovascular health and have a relationship to blood pressure. Suchpulse transit time measurements may also be calibrated againstmeasurement using a traditional blood pressure cuff for increasedaccuracy. This collected data, other data entered by the user, and/orone or both of derived data and analytical status data generatedtherefrom, may be displayed to the user using LCD 1210 or some otheroutput/feedback device such as a screen on a treadmill, headphones wornby the user, or an earpiece such as those worn by first responders.

According to a further alternate embodiment of the present invention,I/O device 1200 may act as a hub or terminal for collection and, in aspecific embodiment, processing data received from a variety of sources.For example, referring to FIG. 46, I/O device 1200 may be used as a hubor terminal in health club 1500 to collect and, in a specificembodiment, process data relating to a user's activities in health club1500 received from a variety of devices located in health club 1500. Inthis embodiment, I/O device 1200 may take the form of a watch-likedevice that is worn by the user on his or her wrist, clipped to theclothing of the user, or otherwise carried by the user. Referring toFIG. 46, I/O device 1200 is in electronic communication with exerciseequipment 1505 through communications connection 1230, which may be awired connection, but which preferably is a wireless connection.Exercise equipment 1505 may be any type of exercise equipment, such as atreadmill or exercise bike, that possesses the ability to generate datarelating to the exercise being done and transmit the data to I/O device1200 over communications connection 1230. I/O device 1200 is thus ableto collect and store data relating to exercise activity such as thecalories expended during a workout or the duration of the workout. Inaddition, I/O device 1200 may be programmed to store settings and/orexercise programs for each of the various types of exercise equipment1505 such that the settings and/or exercise programs may be transmittedover communications connection 1230 to exercise equipment 1505 prior tocommencement of a workout for controlling it during the workout. As afurther alternative, I/O device 1200 may be provided with an artificialintelligence based program or algorithm that modifies, based on theinformation collected by I/O device 1200, the exercise program beingfollowed by the user. As still a further alternative, the settings usedby and/or exercise programs followed by a user can be set or modifiedremotely by a trainer or similar individual and be communicated to I/Odevice from computing device 1515 or through computing device 1515 froma remote source over the Internet, described in detail below. It will beappreciated that I/O device 1200, preferably being portable, is able tocollect and store data from a number of different pieces of exerciseequipment 1505 that are used by the user as he or she moves aroundhealth club 1500, or, as described elsewhere herein, while the user isoutside of health club 1500, for example at home or while traveling.

As seen in FIG. 46, I/O device 1200 may also be in electroniccommunication with sensor device 1201 through communications connection1230, which preferably is a wireless connection, but which may be awired connection such as with a cradle. Thus, as described in greaterdetail in connection with FIGS. 41 through 45, I/O device 1200 is ableto collect and store data relating to the physiological parameters ofthe user before, during and after any exercise activity. For lowbandwidth applications, methods are known for transmitting electronicsignals through the body. Thus, if both I/O device 1200 and sensordevice 1201 are in contact with the user's skin, it may be possible totransmit data using the user's body. Similarly, data may also betransmitted in this manner to other devices by the user by touchingthem. According to an alternate embodiment of the present invention,sensor device 1201 acts as the hub or terminal for collection and, in aspecific embodiment, processing data received from a variety of sources,and as such, would replace I/O device 1200 in FIG. 46.

According to one aspect of the present invention, I/O device 1200 storesa program or regimen preferably including a set of goals that may beestablished by set by the user or a third party such as a trainer orcare giver. I/O device 1200 communicates with and is programmed tocontrol an apparatus in the environment such as a treadmill or weightmachine. Specifically, I/O device 1200 is able to communicateinstructions to the apparatus for setting the apparatus up for thedesired interaction/result, such as choosing treadmill programs orsetting or weight machine weight amounts. While user interacts with theapparatus, I/O device 1200, being in communication with the apparatus,tracks the user's performance, preferably with respect to the program orregimen including goals. The tracking may be based on informationreceived from the apparatus, such as repetitions on a weight machine ordistances run on or heart rate measured by a treadmill, and may also bebased on parameters being measured by sensor device 1201 or I/O device1200 such as energy expenditure. I/O device 1200 may also adjust/controlthe apparatus the user is interacting with to maximize the performancetoward the goal, such as by adjusting the treadmill angle and/orresistance to decrease heart rate or energy expenditure rate of theindividual. Such adjustment may be important if, for example, theindividual is a CVD patient that needs to watch how much they exertthemselves. In addition, after the use of the apparatus is complete, I/Odevice 1200 can adjust the program or regimen so that the next time theuser uses the apparatus, the program or regimen will have been adjustedto comply with the progress or lack of progress the person has made.This adjustment could also include free-living exercise and otherinformation that gets collected between periods of use of the apparatus.For example, if the person walked the rest of the week according totheir program or regimen, the next time they come to use the apparatus,instead of using the same now outdated program/regimen, theprogram/regimen is adjusted to meet the user's new capabilities. Theprinciple just described could also apply to interaction with othertypes of equipment other than exercise equipment, such as medicationdispensers, CPAP machines used in sleep therapy, or even a thermostat inthe house.

Most health clubs include various devices for providing entertainment tousers while they are exercising. For example, a health club may includea number of television monitors, with each monitor providing a differentchannel of programming. Users are able to listen to the audio portionsaccompanying the programming while exercising by plugging headphonesinto an access device provided adjacent to each piece of exerciseequipment, and may use the access device to select among the audioportions of the various programming channels. Referring to FIG. 46, I/Odevice 1200 may be in electronic communication through communicationsconnection 1230 with entertainment equipment 1510, which comprises anaccess device or similar equipment as just described provided adjacentto exercise equipment 1505 that allows a user to select among variousentertainment options. In addition, users may be able to choose to viewand or listen to a prescribed program such as a health education programor a motivational program. I/O device 1200 and entertainment equipment1510 may be adapted to enable I/O device 1200 to collect fromentertainment equipment 1510 and store data relating to the variousentertainment or other programming options selected by the user.

In addition, health club 1500 includes computing device 1515, which maybe a PC or a server computer or the like. I/O device 1200 is adapted tobe in electronic communication with computing device 1515 throughcommunications connection 1230 to enable the data collected, stored and,in a specific embodiment, processed by I/O device 1200 to be transmittedto computing device 1515. For example, a wireless interface device inelectronic communication with computing device 1515 could be placed nearthe front desk of health club 1500. As a user exits health club 1500, heor she could place I/O device 1200 in proximity with the wirelessinternet device and, either automatically or after a further step suchas pressing a button, the data collected, stored and, in a specificembodiment, processed by I/O device 1200 while the user was in healthclub 1500 would be downloaded from I/O device 1200 and transmitted tocomputing device 1515. The data transmitted to computing device 1515 mayalso include data manually entered into I/O device 1200, such as caloricconsumption data. As an alternative, the wireless interface device couldbe replaced by a docking station or a jack device that requires I/Odevice to be physically coupled thereto to establish an electroniccommunications path.

As seen in FIG. 46, computing device 1515 is in electronic communicationwith remote server 1520 through the Internet or a similar computernetwork. Remote server 1520 aggregates data transmitted from computingdevice 1515 for a number of users and, according to a specificembodiment, from similar devices located at other health clubs. In analternate embodiment, data may be transmitted directly from I/O device1200 to remote server 1520, rather than through computing device 1515,by, for example a long range wireless communications protocol such athose used with cell phones or 2-way pagers. Remote server 1520 mayinclude a web server that makes the collected data, such asphysiological, exercise activity, and/or caloric consumption data,available to users over the Internet through computing device 1525 underthe control of the user, such as a PC, cell phone or PDA. The data may,in one embodiment, be presented to users in a form similar to thatdescribed in connection with FIGS. 5 through 11. In addition, remoteserver 1520 may be used to segregate the data collected fromentertainment equipment 1510 and, in a specific embodiment, demographicinformation about the users associated with the data. The segregateddata may be used to track the level of use of each programming channeland provide ratings, similar to Nielsen ratings, for each programmingchannel.

Furthermore, I/O device 1200 may also be used to collect data fromdevices located outside of health club 1500 that have capabilities andfunctionality that are similar to exercise equipment 1505 orentertainment equipment 1510. For example, a user that normallyexercises at health club 1500 may be out of town for a period of timeand, while out of town, may exercise at another facility. I/O device1200 may be used to collect data from exercise and/or entertainmentequipment used at the other facility, provided such equipment hascapabilities and functionality similar to that of exercise equipment1505 and entertainment equipment 1510. I/O device 1200 may also be usedto collect data when a user is exercising or watching or listening tosome sort of programming, as described herein, at home using compatibleequipment. In addition, I/O device 1200 can collect relevant informationwhile the user is not at health club 1500 through ways other than fromcompatible equipment. For example, if a user takes a walk at home, I/Odevice 1200 could collect data relating to the walk from sensor device1201 or from manual entry. When the user returns to health club 1500, heor she can transmit the data collected while he or she was away or whileexercising or engaging in other activities at home to computing device1515, thereby eliminating gaps in data collection that otherwise wouldhave occurred while the user was away from health club 1500. Byeliminating such gaps, a program being followed by the user or goals setby the user can be more accurately monitored and modified, for exampleby a personal trainer or though an artificial intelligence program oralgorithm employed by I/O device 1200.

In one embodiment, I/O device 1200 would store information about theuser including demographic information, identification information,musical preferences, and the type of program they are on, such as rehab,cardio, or fat burning. I/O device 1200 may also collect informationabout the specific room it was in while the person interacted in theclub, when they entered and left the room and what machine they used. Inone specific embodiment, a wireless system may be utilized in which I/Odevice 1200 could understand it's own location in the facility throughmeans of triangulating off two other RF transceivers in the facility.

According to yet another aspect of the present invention, instead of aspace or facility like a health club requiring all the infrastructurefor all it's machines to be networked with one another, either wired orwirelessly, and with a central computer to collect information about andcontrol the machines, people can take I/O device 1200 with them as theyinteract with the space and use it to communicate with the equipmentusing local (not long distance wireless, or wires), low powercommunication methods, so when they use equipment such as a treadmill,I/O device 1200 tracks the machine they were on, the use, how theyperformed, etc. I/O device 1200 may also select entertainment programsthey want to watch and/or listen to. At the end of the session in thespace or facility, the information can be downloaded to a specified sitesuch as the central computer of the facility and/or a remote server.Thus, the space or facility avoided the need to establish a specific andcostly infrastructure to connect up every piece of equipment in thefacility. I/O device acts, instead, as an ad-hoc infrastructure asneeded.

According to one embodiment of the present invention, sensor device1201, which may be any one of sensor device 400 shown in FIGS. 12-17,stand alone sensor device 700 shown in FIG. 21, or sensor device 800shown in FIGS. 22-26, includes a plurality of physiological and/orcontextual sensors. For example, one particular embodiment of sensordevice 400, stand alone sensor device 700, or sensor device 800 includesa t-axis accelerometer, a heat flux sensor, a GSR sensor, a skintemperature sensor, a near-body ambient temperature sensor, and areceiver for receiving heart rate data from a heart rate sensor on, forexample, a chest strap being worn by the user.

One aspect of the present invention relates to a sophisticated algorithmdevelopment process for creating a wide range of algorithms forgenerating information relating to a variety of variables from the datareceived from the plurality of physiological and/or contextual sensorson sensor device 1201. Such variables may include, without limitation,energy expenditure, including resting, active and total values, dailycaloric intake, sleep states, including in bed, sleep onset, sleepinterruptions, wake, and out of bed, and activity states, includingexercising, sitting, traveling in a motor vehicle, blood glucose levels,and lying down, and the algorithms for generating values for suchvariables may be based on data from, for example, the 2-axisaccelerometer, the heat flux sensor, the GSR sensor, the skintemperature sensor, the near-body ambient temperature sensor, and theheart rate sensor in any of the embodiments described above.

Note that there are several types of algorithms that can be computed.For example, and without limitation, these include algorithms forpredicting user characteristics, continual measurements, durativecontexts, instantaneous events, and cumulative conditions. Usercharacteristics include permanent and semi-permanent parameters of thewearer, including aspects such as weight, height, and wearer identity.An example of a continual measurement is energy expenditure, whichconstantly measures, for example on a minute by minute basis, the numberof calories of energy expended by the wearer. Durative contexts arebehaviors that last some period of time, such as sleeping, driving acar, or jogging. Instantaneous events are those that occur at a fixed orover a very short time period, such as a heart attack or falling down.Cumulative conditions are those where the person's condition can bededuced from their behavior over some previous period of time. Forexample, if a person hasn't slept in 36 hours and hasn't eaten in 10hours, it is likely that they are fatigued. Table 3 below shows numerousexamples of specific personal characteristics, continual measurements,durative measurements, instantaneous events, and cumulative conditions.

TABLE 3 personal age, sex, weight, gender, athletic ability,characteristics conditioning, disease, height, susceptibility todisease, activity level, individual detection, handedness, metabolicrate, body composition continual mood, beat-to-beat variability of heartbeats, measurements respiration, energy expenditure, blood glucoselevels, level of ketosis, heart rate, stress levels, fatigue levels,alertness levels, blood pressure, readiness, strength, endurance,amenability to interaction, steps per time period, stillness level, bodyposition and orientation, cleanliness, mood or affect, approachability,caloric intake, TEF, XEF, ‘in the zone’-ness, active energy expenditure,carbohydrate intake, fat intake, protein intake, hydration levels,truthfulness, sleep quality, sleep state, consciousness level, effectsof medication, dosage prediction, water intake, alcohol intake,dizziness, pain, comfort, remaining processing power for new stimuli,proper use of the armband, interest in a topic, relative exertion,location, blood- alcohol level durative exercise, sleep, lying down,sitting, standing, measurements ambulation, running, walking, biking,stationary biking, road biking, lifting weights, aerobic exercise,anaerobic exercise, strength-building exercise, mind-centering activity,periods of intense emotion, relaxing, watching TV, sedentary, REMdetector, eating, in-the-zone, interruptible, general activitydetection, sleep stage, heat stress, heat stroke, amenable toteaching/learning, bipolar decompensation, abnormal events (in heartsignal, in activity level, measured by the user, etc), startle level,highway driving or riding in a car, airplane travel, helicopter travel,boredom events, sport detection (football, baseball, soccer, etc),studying, reading, intoxication, effect of a drug instantaneous eventsfalling, heart attack, seizure, sleep arousal events, PVCs, blood sugarabnormality, acute stress or disorientation, emergency, heartarrhythmia, shock, vomiting, rapid blood loss, taking medication,swallowing cumulative Alzheimer's, weakness or increased likelihood ofconditions falling, drowsiness, fatigue, existence of ketosis,ovulation, pregnancy, disease, illness, fever, edema, anemia, having theflu, hypertension, mental disorders, acute dehydration, hypothermia,being-in-the-zone

It will be appreciated that the present invention may be utilized in amethod for doing automatic journaling of a wearer's physiological andcontextual states. The system can automatically produce a journal ofwhat activities the user was engaged in, what events occurred, how theuser's physiological state changed over time, and when the userexperienced or was likely to experience certain conditions. For example,the system can produce a record of when the user exercised, drove a car,slept, was in danger of heat stress, or ate, in addition to recordingthe user's hydration level, energy expenditure level, sleep levels, andalertness levels throughout a day.

According to the algorithm development process, linear or non-linearmathematical models or algorithms are constructed that map the data fromthe plurality of sensors to a desired variable. The process consists ofseveral steps. First, data is collected by subjects wearing sensordevice 1201 who are put into situations as close to real worldsituations as possible (with respect to the parameters being measured),such that the subjects are not endangered and so that the variable thatthe proposed algorithm is to predict can, at the same time, be reliablymeasured using highly accurate medical grade lab equipment. This firststep provides the following two sets of data that are then used asinputs to the algorithm development process: (i) the raw data fromsensor device 1201, and (ii) the data consisting of the gold-standardlabels measured with the more accurate lab equipment. For cases in whichthe variable that the proposed algorithm is to predict relates tocontext detection, such as traveling in a motor vehicle, thegold-standard data is provided by the subjects themselves, such asthrough information input manually into sensor device 1201, a PC, orotherwise manually recorded. The collected data, i.e., both the raw dataand the corresponding gold standard label data, is then organized into adatabase and is split into training and test sets.

Next, using the data in the training set, a mathematical model is builtthat relates the raw data to the corresponding gold standard labeleddata. Specifically, a variety of machine learning techniques are used togenerate two types of algorithms: 1) algorithms known as featuredetectors that produce a result that is highly correlated with thelab-measured level (e.g. Blood Glucose Level from VO2 level informationfrom a metabolic cart, douglas bag, or doubly labeled water), and 2)algorithms known as context detectors that predict various contexts(e.g., running, exercising, lying down, sleeping, driving) useful forthe overall algorithm. A number of well known machine learningtechniques may be used in this step, including artificial neural nets,decision trees, memory-based methods, boosting, attribute selectionthrough cross-validation, and stochastic search methods such assimulated annealing and evolutionary computation. After a suitable setof feature and context detectors are found, several well known machinelearning methods are used to cross-validate the models using thetraining data and increase the quality of the models of the data.Techniques used in this phase include, but are not limited to,multilinear regression, locally weighted regression, decision trees,artificial neural networks, stochastic search methods, support vectormachines, and model trees.

At this stage, the models make predictions on, for example, a minute byminute basis. Inter-minute effects are next taken into account bycreating an overall model that integrates the minute by minutepredictions. A well known or custom windowing and threshold optimizationtool may be used in this step to take advantage of the temporalcontinuity of the data. Finally, the model's performance can beevaluated on the test set, which has not yet been used in the creationof the algorithm. Performance of the model on the test set is thus agood estimate of the algorithm's expected performance on other unseendata. Finally, the algorithm may undergo live testing on new data forfurther validation.

Further examples of the types of non-linear functions and/or machinelearning method that may be used in the present invention include thefollowing: conditionals, case statements, logical processing,probabilistic or logical inference, neural network processing, kernelbased methods, memory-based lookup (kNN, SOMs), decision lists,decision-tree prediction, support vector machine prediction, clustering,boosted methods, cascade-correlation, Boltzmann classifier, regressiontrees, case-based reasoning, Gaussians, Bayes nets, dynamic Bayesiannetworks, HMMs, Kalman filters, Gaussian processes, algorithmicpredictors (e.g. learned by evolutionary computation or other programsynthesis tools).

Although one can view an algorithm as taking raw sensor values orsignals as input, performing computation, and then producing a desiredoutput, it is useful in one preferred embodiment to view the algorithmas a series of derivations that are applied to the raw sensor values.Each derivation produces a signal referred to as a derived channel. Theraw sensor values or signals are also referred to as channels,specifically raw channels rather than derived channels. Thesederivations, also referred to as functions, can be simple or complex butare applied in a predetermined order on the raw values and, possibly, onalready existing derived channels. The first derivation must, of course,only take as input raw sensor signals, but subsequent derivations cantake as input previously derived channels. Note that one can easilydetermine, from the order of application of derivations, the particularchannels utilized to derive a given derived channel. Also note thatinputs that a user provides on an I/O device or in some fashion can alsobe included as raw signals which can be used by the algorithms. Forexample, the category chosen to describe a meal can be used by aderivation that computes the caloric estimate for the meal. In oneembodiment, the raw signals are first summarized into channels that aresufficient for later derivations and can be efficiently stored. Thesechannels include derivations such as summation, summation ofdifferences, and averages. Note that although summarizing the high-ratedata into compressed channels is useful both for compression and forstoring useful features, it may be useful to store some or all segmentsof high rate data as well, depending on the exact details of theapplication. In one embodiment, these summary channels are thencalibrated to take minor measurable differences in manufacturing intoaccount and to result in values in the appropriate scale and in thecorrect units. For example, if, during the manufacturing process, aparticular temperature sensor was determined to have a slight offset,this offset can be applied, resulting in a derived channel expressingtemperature in degrees Celsius.

For purposes of this description, a derivation or function is linear ifit is expressed as a weighted combination of its inputs together withsome offset. For example, if FOO and BAR are two raw or derivedchannels, then all derivations of the form A*FOO+B*BAR+C, where A, B,and C are constants, is a linear derivation. A derivation is non-linearwith respect to its inputs if it is not expressed as a weighted sum ofthe inputs with a constant offset. An example of a nonlinear derivationis as follows: if (FOO>7) then return BAR*9, else return (BAR*3.5+912).A channel is linearly derived if all derivations involved in computingit are linear, and a channel is nonlinearly derived if any of thederivations used in creating it are nonlinear. A channel nonlinearlymediates a derivation if changes in the value of the channel change thecomputation performed in the derivation, keeping all other inputsconstant. According to a preferred embodiment of the present invention,the algorithms that are developed using this process will have theformat shown conceptually in FIG. 47. Specifically, the algorithm willtake as inputs the channels derived from the sensor data collected bythe sensor device from the various sensors and demographic informationfor the individual as shown in box 1600. The algorithm includes at leastone context detector 1605 that produces a weight, shown as W₁ throughW_(N), expressing the probability that a given portion of collecteddata, such as is collected over a minute, was collected while the wearerwas in each of several possible contexts. Such contexts may includewhether the individual was at rest or active. In addition, for eachcontext, a regression algorithm 1610 is provided where a continuousprediction is computed taking raw or derived channels as input. Theindividual regressions can be any of a variety of regression equationsor methods, including, for example, multivariate linear or polynomialregression, memory based methods, support vector machine regression,neural networks, Gaussian processes, arbitrary procedural functions,etc. Each regression is an estimate of the output of the parameter ofinterest in the algorithm, for example energy expenditure. Finally, theoutputs of each regression algorithm 1610 for each context, shown as A₁through A_(N), and the weights W₁ through W_(N) are combined in apost-processor 1615 which outputs the parameter of interest beingmeasured or predicted by the algorithm, shown in box 1620. In general,the post-processor 1615 can consist of any of many methods for combiningthe separate contextual predictions, including committee methods,boosting, voting methods, consistency checking, or context basedrecombination.

Referring to FIG. 48, an example algorithm for measuring energyexpenditure of an individual is shown conceptually. This examplealgorithm may be run on sensor device 1201 having at least anaccelerometer, a heat flux sensor and a GSR sensor, or I/O 1200 thatreceives data from such a sensor device. In this example algorithm, theraw data from the sensors is calibrated and numerous values basedthereon, i.e., derived channels, are created. In particular, thefollowing derived channels, shown at 1600 in FIG. 48, are computed fromthe raw signals and the demographic information: (1) longitudinalaccelerometer average (LAVE), based on the accelerometer data; (2)transverse accelerometer sum of average differences (TSAD), based on theaccelerometer data; (3) heat flux high gain average variance (HFvar),based on heat flux sensor data; (4) vector sum of transverse andlongitudinal accelerometer sum of absolute differences or SADs (VSAD),based on the accelerometer data; (5) galvanic skin response low gain(GSR), based on the GSR data; and (6) Basal Metabolic Rate (BMR), basedon demographic information. Context detector 1605 consists of a naïveBayesian classifier that predicts whether the wearer is active orresting using the LAVE, TSAD, and HFvar derived channels. The output isa probabilistic weight (W₁ and W₂ for the two contexts rest and active).For the rest context, the regression algorithm 1610 is a linearregression combining channels derived from the accelerometer, the heatflux sensor, the user's demographic data, and the galvanic skin responsesensor. The equation, obtained through the algorithm design process, isA*VSAD+B*HFvar+C*GSR+D*BMR+E, where A, B, C, D and E are constants. Theregression algorithm 1610 for the active context is the same, exceptthat the constants are different. The post-processor 1615 for thisexample is to add together the weighted results of each contextualregression. If A₁ is the result of the rest regression and A₂ is theresult of the active regression, then the combination is justW₁*A₁+W₂*A₂, which is energy expenditure shown at 1620. In anotherexample, a derived channel that calculates whether the wearer ismotoring (driving in a car) at the time period in question might also beinput into the post-processor 1615. The process by which this derivedmotoring channel is computed is algorithm 3. The post-processor 1615 inthis case might then enforce a constraint that when the wearer ispredicted to be driving by algorithm 3, the energy expenditure islimited for that time period to a value equal to some factor (e.g. 1.3)times their minute by minute basal metabolic rate.

This algorithm development process may be used to create algorithms toenable sensor device 1201 to detect and measure various parameters,including, without limitation, the following: (i) when an individual issuffering from duress, including states of unconsciousness, fatigue,shock, drowsiness, heat stress and dehydration; and (ii) an individual'sstate of readiness, health and/or metabolic status, such as in amilitary environment, including states of dehydration, under-nourishmentand lack of sleep. In addition, algorithms may be developed for otherpurposes, such as filtering, signal clean-up and noise cancellation forsignals measured by a sensor device as described herein. As will beappreciated, the actual algorithm or function that is developed usingthis method will be highly dependent on the specifics of the sensordevice used, such as the specific sensors and placement thereof and theoverall structure and geometry of the sensor device. Thus, an algorithmdeveloped with one sensor device will not work as well, if at all, onsensor devices that are not substantially structurally identical to thesensor device used to create the algorithm.

Another aspect of the present invention relates to the ability of thedeveloped algorithms to handle various kinds of uncertainty. Datauncertainty refers to sensor noise and possible sensor failures. Datauncertainty is when one cannot fully trust the data. Under suchconditions, for example, if a sensor, for example an accelerometer,fails, the system might conclude that the wearer is sleeping or restingor that no motion is taking place. Under such conditions it is very hardto conclude if the data is bad or if the model that is predicting andmaking the conclusion is wrong. When an application involves both modeland data uncertainties, it is very important to identify the relativemagnitudes of the uncertainties associated with data and the model. Anintelligent system would notice that the sensor seems to be producingerroneous data and would either switch to alternate algorithms or would,in some cases, be able to fill the gaps intelligently before making anypredictions. Determining when sensors have failed and when data channelsare no longer reliable is a non-trivial task because a failed sensor cansometimes result in readings that may seem consistent with some of theother sensors and the data can also fall within the normal operatingrange of the sensor.

Clinical uncertainty refers to the fact that different sensors mightindicate seemingly contradictory conclusions. Clinical uncertainty iswhen one cannot be sure of the conclusion that is drawn from the data.For example, the accelerometers might indicate that the wearer ismotionless (leading toward a conclusion of “resting”), the galvanic skinresponse sensor might provide a very high response (leading toward“active”), and the heat flow sensor might indicate that the wearer isstill dispersing substantial heat (leading toward “active”). How shouldthese differing factors be assessed? An inferior system would simply tryto vote among the sensors or use similarly unfounded methods tointegrate the various readings. The present invention instead weightsthe important joint probabilities and determines the appropriate mostlikely conclusion (which might be, for this example, that the wearer iscurrently performing or has recently performed a low motion activitysuch as stationary biking).

According to a further aspect of the present invention, a sensor devicesuch as sensor device 400 shown in FIGS. 12-17, stand alone sensordevice 700 shown in FIG. 21, sensor device 800 shown in FIGS. 22-26 orsensor device 1201 shown in FIG. 40, each of which have a processor andeither have one or more sensors or receive signals from one or moresensors, may be used to automatically measure, record, store and/orreport a parameter Y relating to the state of a person, preferably astate of the person that cannot be directly measured by the sensors.State parameter Y may be, for example and without limitation, caloriesconsumed, energy expenditure, sleep states, hydration levels, ketosislevels, shock, insulin levels, physical exhaustion and heat exhaustion,among others. The sensor device is able to observe a vector of rawsignals consisting of the outputs of certain of the one or more sensors,which may include all of such sensors or a subset of such sensors. Asdescribed above, certain signals, referred to as channels, may bederived from the vector of raw sensor signals as well. A vector X ofcertain of these raw and/or derived channels, referred to herein as theraw and derived channels X, will change in some systematic way dependingon or sensitive to the state, event and/or level of either the stateparameter Y that is of interest or some indicator of Y, referred to asU, wherein there is a relationship between Y and U such that Y can beobtained from U. According to the present invention, a first algorithmor function f₁ is created using the sensor device that takes as inputsthe raw and derived channels X and gives an output that predicts and isconditionally dependent on (i) either the state parameter Y or theindicator U, and (ii) some other state parameter(s) Z of the individual.This algorithm or function f₁ may be expressed as follows:f ₂(X)U+Zorf ₂(X)Y+ZAccording to the preferred embodiment, f₁ is developed using thealgorithm development process described elsewhere herein which usesdata, specifically the raw and derived channels X, derived from thesignals collected by the sensor device, so-called gold standard datarelating to U or Y and Z contemporaneously measured using a method takento be the correct answer, for example highly accurate medical grade labequipment, and various machine learning techniques to generate thealgorithms from the collected data. The algorithm or function f₁ iscreated under conditions where the indicator U or state parameter Y,whichever the case may be, is present. As will be appreciated, theactual algorithm or function that is developed using this method will behighly dependent on the specifics of the sensor device used, such as thespecific sensors and placement thereof and the overall structure andgeometry of the sensor device. Thus, an algorithm developed with onesensor device will not work as well, if at all, on sensor devices thatare not substantially structurally identical to the sensor device usedto create the algorithm.

Next, a second algorithm or function f₂ is created using the sensordevice that takes as inputs the raw and derived channels X and gives anoutput that predicts and is conditionally dependent on everything outputby f₁ except either Y or U, whichever the case may be and isconditionally independent of either Y or U, whichever the case may be.The idea is that certain of the raw and derived channels X from the oneor more sensors make it possible to explain away or filter out changesin the raw and derived channels X coming from non-Y or non-U relatedevents. This algorithm or function f₂ may be expressed as follows:f ₂(X)Z and (f ₂(X)Y or f ₂(X)U)Preferably, f₂, like f₁, is developed using the algorithm developmentprocess referenced above. f₂, however, is developed and validated underconditions where U or Y, whichever the case may, is not present. Thus,the gold standard data used to create f₂ is data relating to Z onlymeasured using highly accurate medical grade lab equipment.

Thus, according to this aspect of the invention, two functions will havebeen created, one of which, is sensitive to U or Y, the other of which,f₂, is insensitive to U or Y. As will be appreciated, there is arelationship between f₁ and f₂ that will yield either U or Y, whicheverthe case may be. In other words, there is a function f₃ such that f₃(f₁, f₂)=U or f₃ (f₁, f₂)=Y. For example, U or Y may be obtained bysubtracting the data produced by the two functions (U=f₁−f₂ or Y=f₁−f₂).In the case where U, rather than Y, is determined from the relationshipbetween f₁ and f₂, the next step involves obtaining Y from U based onthe relationship between Y and U. For example, Y may be some fixedpercentage of U such that Y can be obtained by dividing U by somefactor.

One skilled in the art will appreciate that in the present invention,more than two such functions (e.g. f1, f2, f3, . . . f_n−1) could becombined by a last function f_n in the manner described above. Ingeneral, this aspect of the invention requires that a set of functionsis combined whose outputs vary from one another in a way that isindicative of the parameter of interest. It will also be appreciatedthat conditional independence (or dependence) as used here will bedefined to be approximate (in)dependence rather than precise(in)dependence.

The method just described may, for example, be used to automaticallymeasure and/or report the caloric consumption or intake of a personusing the sensor device, such as that person's daily caloric intake,also known as DCI. Automatic measuring and reporting of caloric intakewould be advantageous because other non-automated methods, such askeeping diaries and journals of food intake, are hard to maintain andbecause caloric information for food items is not always reliable or, asin the case of a restaurant, readily available.

It is known that total body metabolism is measured as total energyexpenditure (TEE) according to the following equation:TEE=BMR+AE+TEF+AT,wherein BMR is basal metabolic rate, which is the energy expended by thebody during rest such as sleep, AE is activity energy expenditure, whichis the energy expended during physical activity, TEF is thermic effectof food, which is the energy expended while digesting and processing thefood that is eaten, and AT is adaptive thermogenesis, which is amechanism by which the body modifies its metabolism to extremetemperatures. It is estimated that it costs humans about 10% of thevalue of food that is eaten to process the food. TEF is thereforeestimated to be 10% of the total calories consumed. Thus, a reliable andpractical method of measuring TEF would enable caloric consumption to bemeasured without the need to manually track or record food relatedinformation. Specifically, once TEF is measured, caloric consumption canbe accurately estimated by dividing TEF by 0.1 (TEF=0.1*CaloriesConsumed; Calories Consumed=TEF/0.1).

According to a specific embodiment of the present invention relating tothe automatic measurement of a state parameter Y as described above, asensor device as described above may be used to automatically measureand/or record calories consumed by an individual. In this embodiment,the state parameter Y is calories consumed by the individual and theindicator U is TEF. First, the sensor device is used to create which isan algorithm for predicting TEE. f₁ is developed and validated onsubjects who ate food, in other words, subjects who were performingactivity and who were experiencing a TEF effect. As such, f₁ is referredto as EE (gorge) to represent that it predicts energy expenditureincluding eating effects. The gold standard data used to create f₁ is aVO2 machine. The function f₁, which predicts TEE, is conditionallydependent on and predicts the item U of interest, which is TEF. Inaddition, f₁ is conditionally dependent on and predicts Z which, in thiscase, is BMR+AE+AT. Next, the sensor device is used to create f₂, whichis an algorithm for predicting all aspects of TEE except for TEF. f₂ isdeveloped and validated on subjects who fasted for a period of timeprior to the collection of data, preferably 4-6 hours, to ensure thatTEF was not present and was not a factor. Such subjects will beperforming physical activity without any TEF effect. As a result, f₂ isconditionally dependent to and predicts BMR+AE+AT but is conditionallyindependent of and does not predict TEF. As such, f₂ is referred to asEE (fast) to represent that it predicts energy expenditure not includingeating effects. Thus, f₁ so developed will be sensitive to TEF and f₂ sodeveloped will be insensitive to TEF. As will be appreciated, in thisembodiment, the relationship between f₁ and f₂ that will yield theindicator U, which in this case is TEF, is subtraction. In other words,EE (gorge)−EE (fast)=TEF.

Once developed, functions f₁ and f₂ can be programmed into softwarestored by the sensor device and executed by the processor of the sensordevice. Data from which the raw and derived channels X can be derivedcan then be collected by the sensor device. The outputs of f₁ and f₂using the collected data as inputs can then be subtracted to yield TEF.Once TEF is determined for a period of time such as a day, caloriesconsumed can be obtained for that period by dividing TEF by 0.1, sinceTEF is estimated to be 10% of the total calories consumed. The caloricconsumption data so obtained may be stored, reported and/or used in lieuof the manually collected caloric consumption data utilized in theembodiments described elsewhere herein, such as in connection with FIGS.43A-43H.

Preferably, the sensor device in this embodiment is sensor device 800shown in FIGS. 22-26 that includes and/or is in communication with abody motion sensor such as an accelerometer adapted to generate dataindicative of motion, a skin conductance sensor such as a GSR sensoradapted to generate data indicative of the resistance of theindividual's skin to electrical current, a heat flux sensor adapted togenerate data indicative of heat flow off the body, a body potentialsensor such as an ECG sensor adapted to generate data indicative of therate or other characteristics of the heart beats of the individual, anda temperature sensor adapted to generate data indicative of atemperature of the individual's skin. In this preferred embodiment,these signals, in addition the demographic information about the wearer,make up the vector of signals from which the raw and derived channels Xare derived. Most preferably, this vector of signals includes dataindicative of motion, resistance of the individual's skin to electricalcurrent and heat flow off the body.

As a limiting case of attempting to estimate TEF as described above, onecan imagine the case where the set of additional state parameters Z iszero. This results in measuring TEF directly through the derivationalprocess using linear and non-linear derivations described earlier. Inthis variation, the algorithmic process is used to predict TEF directly,which must be provided as the gold-standard training data.

As an alternative to TEF, any effect of food on the body, such as, forexample, drowsiness, urination or an electrical effect, or any othersigns of eating, such as stomach sounds, may be used as the indicator Uin the method just described for enabling the automatic measurement ofcaloric consumption. The relationship between U and the state parameterY, which is calories consumed, may, in these alternative embodiments, bebased on some known or developed scientific property or equation or maybe based on statistical modeling techniques.

As an alternate embodiment, DCI can be estimated by combiningmeasurements of weight taken at different times with estimates of energyexpenditure. It is known from the literature that weight change(measured multiple times under the same conditions so as to filter outeffects of water retention and the digestive process) is related toenergy balance and caloric intake as follows: (Caloric Intake−EnergyExpenditure)/K=weight gain in pounds, where K is a constant preferablyequal to 3500. Thus, given that an aspect of the present inventionrelates to a method and apparatus for measuring energy expenditure thatmay take input from a scale, the caloric intake of a person can beaccurately estimated based on the following equation: CaloricIntake=Energy Expenditure+(weight gain in pounds*K). This methodrequires that the user weigh themselves regularly, but requires no othereffort on their part to obtain a measure of caloric intake.

Also note also that DCI can be estimated using an algorithm that takessensor data and attempts to directly estimate the calories consumed bythe wearer, using that number of calories as the gold standard and theset of raw and derived channels as the training data. This is just aninstance of the algorithmic process described above.

Another specific instantiation where the present invention can beutilized relates to detecting when a person is fatigued. Such detectioncan either be performed in at least two ways. A first way involvesaccurately measuring parameters such as their caloric intake, hydrationlevels, sleep, stress, and energy expenditure levels using a sensordevice and using the two function (f₁ and f₂) approach described withrespect to TEF and caloric intake estimation to provide an estimate offatigue. A second way involves directly attempting to model fatigueusing the direct derivational approach described in connection withFIGS. 47 and 48. This example illustrates that complex algorithms thatpredict the wearer's physiologic state can themselves be used as inputsto other more complex algorithms. One potential application for such anembodiment of the present invention would be for first-responders (e.g.firefighters, police, soldiers) where the wearer is subject to extremeconditions and performance matters significantly. In a pilot study, theassignee of the present invention analyzed data from firefightersundergoing training exercises and determined that reasonable measures ofheat stress were possible using combinations of calibrated sensorvalues. For example, if heat flux is too low for too long a period oftime but skin temperature continues to rise, the wearer is likely tohave a problem. It will be appreciated that algorithms can use bothcalibrated sensor values and complex derived algorithms.

According to an alternate embodiment of the present invention, ratherthan having the software that implements f₁ and f₂ and determines Uand/or Y therefrom be resident on and executed by the sensor deviceitself, such software may be resident on and run by a computing deviceseparate from the sensor device. In this embodiment, the computingdevice receives, by wire or wirelessly, the signals collected by thesensor device from which the set of raw and derived channels X arederived and determines U and/or Y from those signals as described above.This alternate embodiment may be an embodiment wherein the stateparameter Y that is determined by the computing device is caloriesconsumed and wherein the indicator is some effect on the body of food,such as TEF. The computing device may display the determined caloricconsumption data to the user. In addition, the sensor device may alsogenerate caloric expenditure data as described elsewhere herein which iscommunicated to the computing device. The computing device may thengenerate and display information based on the caloric consumption dataand the caloric expenditure data, such as energy balance data, goalrelated data, and rate of weight loss or gain data.

An embodiment to non-invasively predict blood glucose levels thatutilizes the method, systems, and devices described herein is describedbelow. In this embodiment the state parameter derived (as describedabove) would be blood glucose levels. In an embodiment, the sensordevice described above may be utilized. In a preferred embodiment, sucha sensor device would utilize data related to the heart. Heart rate andheart rate variability measurements add important dimensions to thesensor device's assessment of the subject's metabolism; it has beenestablished that heart rate responds to both changes in metabolism andemotional changes, and heart rate variability changes with respirationrate as well as with numerous other physiological factors. Heart rate,in conjunction with the other measures, enables the sensor device tomore effectively assess stress, fatigue, and blood glucose levels.

A study was performed to assess the effectiveness of such a sensordevice, which employed or contained the processing capabilities of thetype disclosed herein, to determine blood glucose levels. In the study,a sample of 24 subjects was obtained. The study included two majorcomponents: two laboratory visits and a free living period that wasapproximately 24 hours. Blood pressure was obtained at this time. Anyparticipant whose systolic blood pressure was greater than ISO mm hg, orwhose diastolic blood pressure was greater than 90 mm hg was notqualified to remain in the study. For the initial laboratory visit, thesubjects presented to the testing site and the armband was placed. Thesubjects wore the HR enabled sensor device throughout the remainder ofthe study.

Next, a standard 75 gram glucose tolerance was done as follows:

-   -   I) Basal (time zero) blood sugar was obtained with a venous        blood draw.    -   2) In addition AIC was obtained at time zero.    -   3) 75 grams of glucose administered (glucola).    -   4) At 30, 60 and 120 minutes, venous blood was drawn and sent to        the lab for glucose measurement.    -   5) At 15, 45, 75, 90 and 105 minutes, finger stick blood glucose        was measured by blood glucose monitor.    -   6) At the times listed for venous sampling, one drop of the        blood sample was measured by the glucose monitor for calibration        of blood glucose monitors. The patient utilized their usual        pharmacologic methods of glucose control during the glucose        tolerance test.

Blood pressure, pulse, respiration, and blood sugar was determined atthe time of discharge from the first laboratory visit. During the 24hour free-living trial, participants were to perform finger stick bloodglucose levels at a minimum of every four hours during waking hours(before meals and one hour after eating). The participants were torecord both medication taken and activity performed on the logbookprovided by the researchers.

A laboratory visit was scheduled at the end of the 24 hours. At thistime, a set of vital signs were obtained and an exit interview wasconducted to assess patients' responses to the device and to discuss anyevidence of significantly elevated or significant hypoglycemic events.Data analysis was conducted to correlate blood glucose levels with thephysiological parameters collected by the sensor device. This wasperformed in accordance with the standard algorithm developmentpractices described herein. In this study, the goal was first to createan algorithm that can predict blood glucose levels utilizing a singlebaseline measurement. This was done by training the mechanism for doingthis on N−I subjects (where N is the eventual number of compliantsubjects, hopefully 24). This mechanism was then applied to the Nthsubject, and the performance evaluated. This process was repeated foreach subject.

The average correlation and average error per subject was calculated,and compared to an error of 10% of the average obtained glucose reading.The goal was that the error of the predictive algorithm not bestatistically significantly worse than 10%.

Out of the pool of 24 subjects mentioned in the previous section, 20subjects were used for developing glucose estimation algorithms. Four ofthe twenty-four had not yet been integrated at the time of this writingalthough they will be integrated into the final report.

From the subjects included in the analysis, 12 subjects were diagnosedwith Diabetes type I and 7 subjects were diagnosed with type IIDiabetes. Information of one subject's diagnosis was missing.

The age distribution for the subjects ranges from early 20s to mid 70s.Table 4 below demonstrates the age distribution among subjects.

TABLE 4 Age 21-30 31-40 41-50 51-60 61-70 71-80 Number of 2 2 10 3 2 1Subjects

Body Mass Index (BMI) for the subjects included in the analysis rangesfrom 20 to 43. Table 5 below shows the BMI distribution.

TABLE 5 BMI 20-24 25-29 30-34 35-39 >=40 Number of 5 7 6 1 1 Subjects

The subjects used in the analysis had a wide range of fasting bloodglucose levels. Table 6 provides the distribution of fasting bloodglucose levels among the subjects.

Fasting Glucose Level (mg/dl) <50 51-100 101-150 151-200 201-250251-300 >300 Number 1 4 7 2 3 2 1 of Subjects

Glucose prediction model results were evaluated on each subject's24-hour free-living period by performing by-subject cross-validation asdescribed above. The mean glucose level value of all 20 subjects, forthe free-living period was 151.52 mg/dl+/−64.98. The glucose predictionalgorithm estimated the mean glucose value of all subjects to be 153.21mg/dl+/−55.49. The predicted glucose values show a statisticallysignificant correlation with measured glucose values, with a correlationcoefficient of 0.51. The average absolute error in glucose predictionacross all subjects is 46.45 mg/dl or 35.11%. FIG. 49 shows a scatterplot between measured blood glucose level and estimated blood glucoselevels.

Thus, the glucose prediction model provides reasonable correlation withthe original blood glucose values.

Another study was performed on glucose predictions utilizing themethods, devices, and systems disclosed herein. This study was performedon fifteen individuals who are either diagnosed by type-II diabetes, orpre-diabetics. For each subject, the data was obtained by ContinuousGlucose Monitor (CGM) for a period of three days. During the trial,finger stick readings for blood glucose levels were also obtained for4-6 times per day. All subjects wore a sensor device on the back of theupper right arm during the trial. This study relates to an embodiment ofthe invention wherein food-intake information was utilized; therefore, afood log was maintained and used for developing the glucose estimationmodels. The variables for modeling were selected specifically for eachsubject, keeping personalization in mind. Then, equations for estimatingblood glucose values were developed from the data and evaluated by usingby-subject cross-validation.

The results were as follows: the absolute average error betweenestimated Glucose values and CGM values was 21.1 ml/dl (14.1%) and thecorrelation between them was 0.77. The correlation between the modelestimates and the finger stick glucose values was 0.87 and the averageerror between them was 21.30 ml/dl (15.7%). As shown in FIGS. 50A and50B, a Clarke error grid analysis between model estimates and CGM valuesyielded 97.33% points falling in zone A and B (81% in zone A). In thisembodiment, a food log data was utilized in model. FIG. 51 shows thecontribution of the sensor-based variables and the food-intake-basedvariables. As can be seen in the FIG. 51, the sensor-based variables hada contribution of 62% and the food-intake-based variables had acontribution of 38%. Thus, this study concludes that the inventiondescribed herein provides capability to monitor blood glucose levelchanges continuously during free-living conditions, and that practicingsensors alone (without food logging) contribute significantly to theglucose level prediction.

Other embodiments however require only sensor data from the system anddevice disclosed herein and thus do not require food-intake data orfinger-stick glucose data to yield a prediction of blood glucose levels,thus achieving a truly non-invasive method, system, and device fordetermining blood glucose values. A separate study was done with tensubjects. As shown in FIG. 52, a Clarke error grid analysis betweenmodel estimates (for this particular embodiment) and CGM values yielded96.93% points falling in zone A and B (67.8% in zone A). In FIG. 53, aClarke error grid analysis between model estimates (for this particularembodiment) and finger stick values yielded 100% points falling in zoneA and B (64.6% in zone A).

As disclosed above, embodiments of the present invention can include avariety of methods and systems which can be implemented using aconventional general purpose or a specialized digital computer(s) ormicroprocessor(s), programmed according to the teachings of the presentdisclosure. Processing capability may be in the sensor device, or in acomputing device such as personal computer, personal digital assistant,cell phone, etc. The computing device may be the I/O described above. Insum, there are various locations at which the processing may take placedepending on the particular situation.

Appropriate software coding can readily be prepared by programmers basedon the teachings of the present disclosure. Embodiments of the presentinvention can include a computer readable medium, such as a computerreadable storage medium. The computer readable storage medium can havestored instructions which can be used to program a computer to performany of the features presented herein. The storage medium can include,but is not limited to, any type of disk including floppy disks, opticaldiscs, DVDs, CD-ROMs, microdrives, and magneto-optical disks, ROMs,RAMs, EPROMs, EEPROMs, DRAMs, flash memory or any media or devicesuitable for storing instructions and/or data.

The present invention can include software for controlling both thehardware of a computer, such as a general purpose/specializedcomputer(s) or microprocessor(s), or a wearable sensing device; and forenabling them to interact with a human user or other mechanism utilizingthe results of the present invention. Such software can include, but isnot limited to, device drivers, operating systems, executionenvironments/containers, user interfaces, and user applications.

Embodiments of the present invention can include providing code forimplementing processes of the present invention. The providing caninclude providing code to a user in any manner. For example, theproviding can include transmitting digital signals containing the codeto a user; providing the code on a physical media to a user; or anyother method of making the code available.

Embodiments of the present invention can include a computer implementedmethod for transmitting the code which can be executed at a computer toperform any of the processes of embodiments of the present invention.The transmitting can include transfer through any portion of a network,such as the Internet; through wires, the atmosphere or space; or anyother type of transmission. The transmitting can include initiating atransmission of code; or causing the code to pass into any region orcountry from another region or country. A transmission to a user caninclude any transmission received by the user in any region or country,regardless of the location from which the transmission is sent.

Embodiments of the present invention can include a signal containingcode which can be executed at a computer to perform any of the processesof embodiments of the present invention. The signal can be transmittedthrough a network, such as the Internet; through wires, the atmosphereor space; or any other type of transmission. The entire signal need notbe in transit at the same time. The signal can extend in time over theperiod of its transfer. The signal is not to be considered as a snapshotof what is currently in transit.

The foregoing description of preferred embodiments of the presentinvention has been provided for the purposes of illustration anddescription. It is not intended to be exhaustive or to limit theinvention to the precise forms disclosed. Many modifications andvariations will be apparent to one of ordinary skill in the relevantarts. For example, steps performed in the embodiments of the inventiondisclosed can be performed in alternate orders, certain steps can beomitted, and additional steps can be added. It is to be understood thatother embodiments of the invention can be developed and fall within thespirit and scope of the invention and claims. The embodiments werechosen and described in order to best explain the principles of theinvention and its practical application, thereby enabling others ofordinary skill in the relevant arts to understand the invention forvarious embodiments and with various modifications that are suited tothe particular use contemplated. It is intended that the scope of theinvention be defined by the following claims and their equivalents.

What is claimed is:
 1. A system for non-invasively predicting datarelated to an individual's glucose levels, the system comprising: awearable sensor device comprising: (i) a heart sensor in non-invasivecontact with the individual's body and generating data indicative of theindividual's heart when the sensor device is worn by the individual,(ii) an accelerometer in non-invasive contact with the individual's bodyand generating data indicative of the individual's movement when thesensor device is worn by the individual, (iii) a galvanic skin responsesensor generating data indicative of the resistance of the individual'sskin to an applied electric current, (iv) a heat flux sensor generatingdata indicative of the rate of flow of heat off the individual's body,and (v) a processor in electronic communication with the heart sensor,the accelerometer, the galvanic skin response sensor, and the heat fluxsensor, the processor programmed to utilize the data from the heartsensor, the accelerometer, the galvanic skin response sensor, and theheat flux sensor to generate output comprising a prediction of theindividual's blood glucose level.
 2. The system of claim 1 wherein thedata indicative of the individual's heart is heart rate.
 3. The systemof claim 1 wherein the data indicative of the individual's heart isheart rate variability.
 4. The system of claim 1 wherein the output isdetermined by the use of an algorithm.
 5. The system of claim 4 whereinthe algorithm correlates an individual's invasively-measured bloodglucose with the data generated by said sensor device, the sensor devicebeing worn by the individual whose blood glucose levels areinvasively-measured.
 6. The system of claim 1 wherein the processor isfurther programmed to utilize data related to the individual's foodintake to generate the output comprising a prediction of theindividual's blood glucose level.
 7. The system of claim 1 wherein theheart sensor and the accelerometer continuously generate data.
 8. Thesystem of claim 1, wherein the processor requires only data from theheart sensor, the accelerometer, the galvanic skin response sensor, andthe heat flux sensor to generate the prediction of the individual'sglucose level.
 9. The system of claim 1, wherein the galvanic skinresponse sensor and the heat flux sensor are in non-invasive contactwith the individual's body.